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Job Description Job Description Senior AI Engineer Location: New York City Work Style: Hybrid Onsite Employment Type: Full-time Focus: AI, LLMs, Clinical Reasoning, Evaluation, Retrieval, Applied ML About Our Client Our client is building AI technology with the mission of making high-quality healthcare more accessible, affordable, and scalable. Their AI-powered clinical platform already supports millions of patient consultations, and the company is working toward scaling that impact significantly while continuing to improve clinical safety, reasoning quality, accuracy, and trust. This is an opportunity to join a team building real-world clinical AI systems used by patients every day. The company operates in a live healthcare environment, giving the team a unique dataset and feedback loop to test, improve, and deploy AI systems in practical clinical care. About the Role Our client is hiring a Senior AI Engineer to help build the next generation of clinical AI systems. This role blends research and engineering. The ideal candidate is not just running experiments or writing notebooks - they are building real systems that reason, retrieve evidence, evaluate performance, and improve over time. You'll work on agentic reasoning, retrieval, evaluation infrastructure, model learning, and clinical decision support systems. The goal is to help every component of the AI platform become safer, more accurate, more useful, and more trustworthy with each iteration. What You'll Do Design and build agentic clinical reasoning systems Develop AI architectures that support reasoning, reflection, verification, tool use, routing, uncertainty handling, and escalation Build systems where specialized agents and models work together to support safe and reliable clinical decisions Create evaluation platforms, rubrics, simulations, and experiments to measure AI performance in clinical use cases Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes Apply methods such as fine-tuning, distillation, reinforcement learning, preference optimization, and prompt or system optimization Build training data, feedback, reward, and experimentation pipelines Develop search, ranking, retrieval, and grounding algorithms tied to trusted medical evidence and patient context Improve retrieval systems based on their impact on downstream clinical decisions, not just document relevance Own problems end-to-end, from framing and experimentation through shipping and measurement Collaborate closely with engineering, clinical, product, and physician-scientist partners What We're Looking For Strong experience building real AI, ML, or LLM-powered systems Deep experience in at least two of the following areas: Agentic architectures, reasoning systems, and tool use Model evaluation, experimentation, and rubric design Model training, fine-tuning, distillation, or reinforcement learning Search, ranking, retrieval, RAG, or grounding systems Strong ML fundamentals, including training data, objectives, metrics, failure analysis, calibration, and validation Ability to work in complex domains where ground truth is incomplete and expert opinions may differ Strong engineering fundamentals with experience building production systems, not just research prototypes Clear communication and strong collaboration across engineering, clinical, and product teams Ability to think through business impact and prioritize technical work accordingly Comfort operating with autonomy in a builder-first environment Experience Profile Successful candidates will typically have one of the following backgrounds: Advanced degree in a quantitative, computational, scientific, or related discipline with 3+ years of highly relevant applied AI/ML or research experience 7+ years of relevant experience building and researching ML systems Recent hands-on work with LLMs, generative AI, agentic systems, retrieval systems, or production AI infrastructure Our client cares more about the depth and quality of your work than a specific credential or traditional career path. Bonus Experience Published research, patents, meaningful open-source contributions, or novel production ML systems Experience building AI systems at an early-stage or high-growth company Experience in healthcare, clinical AI, regulated industries, or safety-critical environments Familiarity with clinical workflows, healthcare data, HIPAA, FHIR, EHR systems, or HL7 Experience with human-feedback systems, RLHF, simulations, or synthetic data generation Experience with AI safety, bias detection, calibration, fairness, or model reliability Why This Opportunity Build AI systems that can meaningfully improve access to healthcare Work on real clinical AI problems with real patient usage and feedback Join a team focused on reasoning, retrieval, evaluation, safety, and trust Work side by side with physician-scientists and experienced technical builders Own high-impact AI systems end-to-end Operate with autonomy in a fast-moving, builder-first environment Contribute to technology designed to scale from millions of consultations to much larger clinical impact Compensation & Benefits Competitive salary Meaningful equity with upside as the company grows Comprehensive health benefits High autonomy and ownership over important technical problems Opportunity to build AI systems transforming healthcare at scale Ideal Candidate Profile The ideal candidate is a research-minded AI engineer who wants to build intelligent systems that work in the real world. They care deeply about reasoning quality, evaluation, safety, and measurable improvement - and they have the engineering ability to turn ambitious ideas into production systems. This person is excited by the challenge of building clinical AI that can earn trust over time.

Job Description Job Description Role: Mid - Senior Machine Learning Engineer (This role is open to US Citizens, Green Card holders, GC-EAD only. We do not sponsor visas.) Summary: Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced machine learning models, with a special emphasis on Generative AI. In this role, you will craft and refine AI-driven solutions, turning innovative ideas into value-adding features and services, thereby solidifying our market leadership and technological forefront for our clients. About Adidev Technologies Inc. Adidev Technologies,() is a premier IT consulting firm delivering top-notch, Machine Learning Engineer, iOS and Android, data scientist, Developer solutions to industry giants including Delta, Google, Apple, Spotify, US Bank, FedEx, and more. We're not just a software consulting company - we're a dynamic force shaping the future of technology. Partnering with industry giants, we consistently deliver groundbreaking solutions that redefine the digital landscape. As we continue to expand our footprint, we're on the hunt for exceptional individuals who can bring their technical prowess to our team and elevate our projects to new levels of innovation. Expertise: We excel in IT consultative services and quality engineer development, with Good years of experience. Global Presence: Our diverse employee workforce spans four continents. Proven Track Record: Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects across the USA. How We'll Guide You Teaching and Development: We are dedicated to nurturing your growth and development, shaping you into an exceptional consultant capable of delivering top-tier solutions to our end clients. Custom Support: An array of teams, from Development Managers to Tech Subject Matter Experts, are dedicated to your success. Project Placement: A market-expertise team ensures you secure and thrive in projects with our esteemed clients. Career Growth: We facilitate industry experience to propel your technical journey forward. Key Responsibilities: Architect and refine sophisticated ML models and algorithms, translating complex datasets into actionable solutions. Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring. Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions. Lead cross-functional collaborations to integrate Generative AI models into our offerings, enhancing product capabilities and user experiences. Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement. Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency. Conduct exploratory data analysis to extract valuable insights and influence strategic decisions. Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks. Promote compliance with industry standards and regulatory requirements, emphasizing ethical AI practices. Requirements: Degree in Computer Science, Engineering, Statistics, or a related technical field. Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI domains. Demonstrable experience with Generative AI models and frameworks, such as GANs or Transformers, applied in industry settings. Practical experience with SQL/NoSQL databases, data visualization tools, and version control systems. Strong foundational understanding of algorithmic complexity and data structure optimization. Excellent problem-solving, collaboration, and communication abilities. Develop and implement cutting-edge machine learning models, with a particular focus on Generative AI applications such as text generation, image synthesis, and creative AI. Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions. Stay ahead of AI research, especially in Generative AI, applying the latest findings and techniques to drive innovation within our projects. Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn). Strong background in cloud computing and big data platforms (AWS, Azure, GCP), with hands-on experience in cloud-based ML services and serverless architectures. Familiarity with DevOps for AI, including containerization (Docker, Kubernetes), CI/CD pipelines, and MLOps practices. Facilitate knowledge sharing and best practices in AI/ML, particularly focusing on Generative AI, within the team. Ensure all AI implementations are compliant with ethical guidelines and data privacy standards. How to Apply: Interested candidates are invited to submit a comprehensive application, including a latest updated resume and a detailed cover letter, showcasing your expertise. Perks and Beyond! Competitive salary range: Based on experience and market value Pack your bags! Paid relocation is on us. Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to Embark? we invite you to take this extraordinary step with us. Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a curated selection of your most influential projects. At Adidev Technologies, we're dedicated to shaping your success. Join us to craft a future powered by innovation and growth. Note: Adidev Technologies Inc. is a staunch advocate of diversity and equal opportunity. We warmly welcome applications from candidates of all backgrounds, experiences, and walks of life. Your unique perspective could be the catalyst for our next revolutionary breakthrough

Job Description Job Description Curinos empowers financial institutions to put customers at the center of every decision. Our AI-first platform transforms proprietary data, advanced analytics and deep financial services expertise into timely recommendations - delivered right where teams work. The result: confident decisions, stronger customer relationships, and lasting, profitable growth. Curinos operates under a hybrid modality and has office locations in New York, Chicago, Boston, Toronto, and London. This role is open to hybrid/ remote candidates based in the United States. Job Description We are seeking a Senior ML/AI Platform Engineer to help build and operate Curinos' Databricks-native AI platform. This role sits at the intersection of machine learning engineering, platform engineering, and site reliability, with a focus on enabling reliable deployment and operation of AI and ML systems at scale. This is a high-impact role that will unlock the next phase of Curinos scalable growth. You will be responsible for designing and implementing the infrastructure, tooling, automation, observability, and governance capabilities that power production machine learning models, LLM applications, and agentic AI workflows. You will work with applied scientists to move solutions from experimentation to production quickly, safely, and repeatably. You will "build it once and scale it many times." We are a Databricks-first organization and make extensive use of Databricks Workflows, Asset Bundles, Unity Catalog, MLflow, Delta Live Tables, and related ecosystem tools. You will work closely with data scientists, data engineers, software engineers, and product teams embed AI and ML capabilities into our products, as well as automate operational processes to achieve reliable, scalable efficiencies across data and algorithmic workflows company-wide. As a FinTech company operating in a regulated environment, we place strong emphasis on governance, reproducibility, observability, and operational excellence. This role is critical to ensuring our AI platform and ML solutions meet those standards while remaining fast-moving and developer-friendly. Responsibilities Design, build, and maintain platform capabilities for deploying, monitoring, and operating ML models, LLM applications, and agentic AI workflows. Develop automated CI/CD pipelines and infrastructure-as-code patterns for AI and machine learning workloads. Create platformtoolingthatstandardizes deployment practicesof AI and ML capabilitiesacross teams. Build observability solutions that track model health, service reliability, cost, performance, AI safety metrics, and business outcomes. Implement scalable evaluation and monitoring frameworks for LLMs, agentic workflows, and generative AI applications. Partner withscientists and engineers toproductionizenewMLmodels and AI capabilities. Support governance, auditability, reproducibility, and model lifecycle management requirements. Strongly advocate and demonstrateoperational excellence practices includingplatform automation,reliability improvements,incident response, root cause analysis. Design, revise, and document architecture patterns, operational procedures, and engineering best practices. Salary Range: $ 130,000- $147,000 USD (plus bonus Desired Skills & Experience Strong experience building and operating ML, AI, data, or cloud platforms in production environments. Deep hands-on expertise with Databricks, including Workflows, Delta Lake, Delta Live Tables, Unity Catalog, Asset Bundles,MLflow, Python,PySpark, andSparkSQL. Experience with modernMLOpspractices including CI/CD, automated testing, model deployment, feature management, observability, and governance. Experience working with LLMs, agentic AI systems, evaluation frameworks, AI safety controls, and model monitoring solutions. Experience with model serving architectures, APIs, MCP servers, and scalable inference systems. Understanding of production support, incident management, and operational excellence practices. Strong communication skills and the ability to work effectively across multidisciplinary teams that make use of the AI and ML workflows you build. Why work at Curinos? Competitive benefits, including a range of Financial, Health and Lifestyle benefits to choose from Flexible working options, including home working, flexible hours and part time options, depending on the role requirements - please ask! Unlimited PTO policy, floating holidays, volunteering days and a day off for your birthday Learning and development tools to assist with your career development Work with industry leading Subject Matter Experts and specialist products Regular social events and networking opportunities Collaborative, supportive culture, including an active DE&I program Employee Assistance Program which provides expert third-party advice on well-being, relationships, legal and financial matters, as well as access to counselling services Applying We know that sometimes the 'perfect candidate' doesn't exist, and that people can be put off applying for a job if they don't meet all the requirements. If you're excited about working for us and have relevant skills or experience, please go ahead and apply. You could be just what we need! If you need any adjustments to support your application, such as information in alternative formats, special requirements to access our buildings or adjusted interview formats please contact us at and we'll do everything we can to help. Inclusivity at Curinos We believe strongly in the value of diversity and creating supportive, inclusive environments where our colleagues can succeed. As such, Curinos is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, color, ancestry, national origin, religion, or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other protected characteristics.

Job Description Job Description Most of what makes American healthcare expensive isn't medical care. It's the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial. Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut. AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves. We're already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators. About the Role Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring a Senior MLOps Engineer to build and own the infrastructure that powers it - from training models on tens of millions of patients and hundreds of millions of rows of claims data, to serving real-time quotes in seconds against inference-time datasets that run into the trillions of rows. You'll also build the tooling that lets our data scientists and actuaries iterate faster than ever. This is an ML infrastructure role with real room to do ML and data science. You'll own the platform, but you'll also have the opportunity to work alongside our data scientists and actuaries to test and evaluate your own ideas - not just support theirs. What You'll Work On Training infrastructure for underwriting Build and own the infrastructure layer that powers our underwriting model, trained on tens of millions of patients and hundreds of millions of rows of claims data. Make training reliable, reproducible, and scalable as data volume and model complexity grow. Real-time inference for quoting Build and own the API layer that produces quotes in seconds - serving a trained model against a much larger inference-time dataset, on the order of trillions of rows of claims across hundreds of millions of people. Own the latency, reliability, and scalability of the serving path the quoting product depends on. Accelerate data science iteration Make it as easy as possible for data scientists and actuaries to test new features and ideas. Build backtesting and validation infrastructure so model performance can be measured quickly and trustworthily. Remove friction from the path between an idea and a validated, production-ready model - make experimentation simpler than it's ever been. What We're Looking For A strong track record building ML or data infrastructure in production at scale. Deep proficiency in Python, with comfort in processing large datasets (Spark, Databricks, or equivalent). Experience with model training pipelines and/or low-latency model serving in production. Experience building tooling that makes other people faster - feature testing, experiment tracking, backtesting, or similar developer/researcher -facing infrastructure. The ability to own systems end-to-end, set standards, and operate reliable production infrastructure (SLAs, monitoring, on-call). Genuine interest in the modeling itself - you want to occasionally get your hands into the data science, not only the infrastructure. Nice to Have Prior experience in a regulated space like healthcare or insurance. Experience with MLOps tooling (MLflow or similar), feature stores, or experimentation platforms. Experience supporting data science or actuarial teams in production environments. Compensation $180,000 - $230,000 + equity Why Join Arlo: High ownership: You'll get real responsibility from day one-our high-trust team empowers you to run with big problems and shape core parts of the company. Join an important mission: Your work directly influences how people access care and improves lives at scale. Growth & expansion: We're moving fast, and as we grow, your scope will grow with us-new challenges, bigger opportunities, and rapid career velocity. Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you'll use AI to fundamentally reimagine how people get healthcare. High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition. Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process. Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law. Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: .

Job Description Job Description Tiger Analytics is seeking a highly skilled Senior AI Engineer to join our dynamic team. In this role, you will design, develop, and implement cutting-edge AI solutions that drive business value for our clients. You will leverage advanced machine learning techniques, frameworks, and large datasets to create innovative products and solutions. As a Senior AI Engineer, you will work closely with cross-functional teams to identify project requirements, define success metrics, and maintain high-quality standards. Your expertise in AI will play a critical role in shaping our product offerings and ensuring the successful deployment of AI models in production. The successful candidate will have a solid background in artificial intelligence, experience with various ML frameworks, and a passion for solving complex business problems. Requirements Key Responsibilities: Design and implement AI algorithms and models to solve real-world problems. Collaborate with data scientists, data engineers, and business analysts to understand project requirements and propose relevant AI solutions. Monitor and analyze the performance of AI models in production and iterate on them to improve outcomes. Develop technical documentation as well as customer-facing documentation and presentations. Stay updated with the latest research and trends in AI and propose innovative ideas to improve our offerings. Qualifications: Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field. 5+ years of experience in AI/ML development with demonstrated success in deploying machine learning models to production. Proficiency in programming languages such as Python and familiarity with libraries such as TensorFlow, PyTorch, and Scikit-learn. Experience with cloud-based AI services such as AWS, Google Cloud, or Azure. Strong analytical and problem-solving skills, with a proven ability to interpret business requirements into technical solutions. Excellent communication skills and ability to convey complex technical concepts to non-technical stakeholders. Preferred Skills: Experience with natural language processing (NLP) or computer vision applications. Knowledge of MLOps principles and tools. Familiarity with version control systems (e.g., Git) and Agile methodologies. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Job Description Job Description Why Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection-between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you. About the Role Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our ML and AI capabilities are expanding rapidly-powering recommendation systems, clinical decision support, agentic AI products, and developer tooling-and the infrastructure underneath needs to scale with them. As our first dedicated ML Platform Engineer, you'll define the technical direction and build the foundational systems that our data scientists, ML engineers, and product teams depend on to ship AI-powered features reliably and at scale. We have several models in production today and are investing in hosted GPU inference to support the next generation of our AI capabilities. You'll inherit and evolve existing infrastructure while building new platform capabilities-from multi-tenant model serving and GPU inference pipelines to multimodal data management, evaluation frameworks, observability, and infrastructure as code. You'll own the platform layer that makes ML/AI development at Charlie Health fast, safe, and repeatable as the team grows. If you care about building the systems that let others build great things, this team is for you. Responsibilities Infrastructure & Serving Define technical direction for ML/AI infrastructure and make build-vs-buy decisions as the founding platform engineer Design and operate multi-vendor AI infrastructure supporting client-facing and clinician-facing LLM applications across multiple LLM providers Design, build, and operate production model serving systems; maintain infrastructure as code for reproducible ML environments, training pipelines, and deployment workflows Develop high-performance GPU inference pipelines with low latency and high availability Own the multimodal data pipeline layer-manage ingestion, processing, and serving of text, audio, and structured clinical data for ML and AI systems AI Systems & Tooling Create reliable infrastructure for agentic AI systems, including orchestration, monitoring, evaluation, and observability tooling Build developer tooling that accelerates data science and ML engineering workflows across the organization Observability & Operations Own AI observability-build monitoring, alerting, and debugging capabilities for production ML systems Partner with ML engineers, data scientists, and product teams to understand infrastructure needs and translate them into scalable platform capabilities Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing Participate in our on-call rotation to ensure model serving uptime, pipeline reliability, and infrastructure health Requirements 4+ years of professional experience in software engineering, with at least 2 years focused on ML infrastructure, ML platform, or AI systems engineering Strong software engineering fundamentals in Python and deep infrastructure expertise Familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, or similar) and CI/CD for ML pipelines Experience with infrastructure as code (Terraform, Pulumi, or similar) and container orchestration (Kubernetes, ECS) Experience building evaluation and observability systems for LLM-based or agentic AI applications is a plus Excellent at managing ambiguity-able to break down big, messy problems into smaller parts with tractable solutions and clear iterations Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun Experience with a systems language (Go, Rust, or C++) is a plus This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC. Benefits Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here. The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. Our Values Connection: Care deeply & inspire hope. Congruence: Stay curious & heed the evidence. Commitment: Act with urgency & don't give up. Please do not call our public clinical admissions line in regard to this or any other job posting. Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: -openings. Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent email addresses. Legitimate emails will never originate from or other commercial email services. Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals. At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people. Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation. By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service. By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.

Job Description Job Description Founding Forward Deployed Engineer Location: Tribeca, New York City Employment Type: Full-time Work Arrangement: On-site, 5 days per week Salary: $180,000-$250,000 base Equity: Competitive equity Visa: Open to eligible visa transfers, including H-1B and OPT Relocation: Up to $10,000 for candidates relocating from outside New York About the Opportunity A well-capitalized, post-revenue enterprise AI company is hiring a Founding Forward Deployed Engineer to lead the technical deployment of its platform within complex customer environments. The company is building an AI-powered revenue execution platform that helps enterprise teams identify which customers to prioritize, understand why, and determine what actions to take next. Its technology combines large language models with structured customer data to automate account scoring, customer segmentation, and revenue-expansion workflows. Already working with Fortune 500 customers and generating meaningful revenue, the company is scaling with a lean, highly technical founding team. This hire will own one of the most important paths in the business: turning messy customer data and institutional knowledge into reliable, production-ready AI workflows. What You'll Do Own enterprise customer deployments from initial data access through production launch and measurable value delivery. Explore undocumented data warehouses and map complex or legacy schemas to business concepts such as churn, retention, expansion, and annual recurring revenue. Interview customer stakeholders to understand business logic, reconcile conflicting definitions, and translate institutional knowledge into validated SQL queries. Build and validate the semantic and ontology layers that power customer-facing AI agents. Develop, deploy, and maintain production data pipelines and agent workflows within customer environments. Independently write code, diagnose technical issues, and deploy systems without extensive oversight. Monitor deployed workflows, validate their outputs, and ensure they produce measurable customer outcomes. Manage two to three customer engagements simultaneously while collaborating directly with customer data, engineering, and business teams. Use and help improve internal agent tooling, evaluation frameworks, validation processes, and guardrails. Balance customer communication with highly detailed technical execution; approximately 70-80% of the role involves hands-on data exploration, transformation, and verification. What We're Looking For Approximately 2-5 years of experience as a Forward Deployed Engineer, Customer Engineer, Solutions Engineer, customer-facing Software Engineer, or in a closely related technical role. Experience owning end-to-end technical customer deployments involving data access, schema mapping, stakeholder management, production delivery, and value validation. Deep SQL and data-warehouse fluency, including the ability to navigate messy, legacy, or undocumented schemas independently. Experience with dbt, data pipelines, data warehouses, or comparable production data systems. Strong hands-on programming skills, ideally in Python, with experience independently building, debugging, and deploying production systems. An AI-native working style, including regular use of tools such as Claude or Cursor. Experience building or customizing agent-driven workflows, not simply using off-the-shelf AI tools. Applied data-science literacy, including familiarity with distributions, seasonality, validation design, and distinguishing meaningful findings from noise. Ability to translate ambiguous business requirements into reliable technical systems and validated data models. Strong customer-facing communication skills, including the ability to defend technical decisions under pressure and change direction when presented with better evidence. High tolerance for detail-oriented and repetitive data-verification work. A bachelor's degree in computer science, data science, statistics, or another quantitative STEM discipline. A strong academic pedigree or experience at a recognizable technology, data, consulting, or financial-services organization; candidates should have at least one of these indicators. Willingness to work on-site in New York City five days per week. Strong Candidate Backgrounds You may be especially well suited for this role if you have worked as: A Forward Deployed Engineer, Customer Engineer, or Solutions Engineer at a leading data or AI company. An Analytics Engineer or Data Scientist who transitioned into customer-facing implementation and delivery. A technical consultant with a genuine computer science foundation and hands-on engineering experience. An early-stage startup engineer who independently owned customer deployments and production systems. What Will Help You Stand Out Experience working at an early-stage startup, ideally from Seed through Series B. Experience deploying LLM-powered products or AI agents in production. Experience building evaluation frameworks, validation systems, semantic data layers, or signal-processing systems. Founder or founding-engineer experience. A track record of succeeding in ambiguous, fast-moving environments without extensive direction. Genuine enthusiasm for detailed data investigation, testing, and verification. Why Join Join a lean founding team tackling a multibillion-dollar gap in enterprise software. Help shape a platform already serving major enterprise customers. Own a critical, high-impact function rather than inheriting a narrow piece of an established system. Work directly with company leadership, engineering, and customers. Receive an aggressive compensation package with competitive equity. Comprehensive medical, dental, and vision coverage for employees and their families. Parental leave, a monthly wellness stipend, daily lunches and snacks, and a flexible vacation policy. Up to $10,000 in relocation support for candidates moving from outside New York. Client Interview Process Culture and experience interview Technical interview Half-day on-site working simulation based on a realistic customer deployment scenario

Job Description Job Description Location: Indianapolis, IN Metro (Hybrid / 3-Day Onsite) (Open to Regional/EST Candidates with Onsite Travel) Contract Type: Contractor Full-Time / Enterprise Project Engagement (Outsourced via Xenon7) About Xenon7 Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth. Job Summary We are seeking a Senior Machine Learning Engineer with extensive experience in production MLOps, model deployment, and system scaling to drive ML engineering initiatives for a top-tier life sciences client. This role sits at the critical intersection of production ML infrastructure, life science research, and manufacturing process engineering. In this position, you will own the architectural design and hands-on execution of production ML systems, model integration APIs, and scalable MLOps pipelines. You will bridge complex domains-from computational biology, small and large molecule research, and clinical trial analytics to active pharmaceutical ingredient (API) manufacturing processes, batch optimization, and industrial automation ML. Operating in a 3-day onsite hybrid capacity in Indianapolis, you will collaborate directly with process engineers, life science researchers, and platform engineering teams to build robust, low-latency ML systems that scale across the enterprise. Key Responsibilities Production MLOps & Systems Architecture Design, deploy, and maintain robust, production-grade MLOps pipelines and infrastructure for continuous model training, deployment, versioning, and monitoring. Implement automated model drift detection, performance monitoring, and self-healing inference pipelines in high-reliability environments. Process Engineering & Manufacturing ML Integration Operationalize and integrate production ML models into operational technology (OT), API manufacturing workflows, and chemical process control systems. Deploy predictive models for batch processing, process control optimization, real-time quality assurance, and facility automation use cases. Scalable Inference & System Integration Build low-latency, high-throughput microservices and serving architectures (FastAPI, Triton Inference Server, TorchServe) for model deployment into live production applications. Containerize and orchestrate ML workloads across distributed cloud and edge systems using Kubernetes, Docker, and modern pipeline engines (Kubeflow, MLflow). Technical Leadership & Domain Alignment Partner directly with chemical engineers, computational biologists, and software architects to translate operational friction into production-ready ML engineering solutions. Establish enterprise MLOps standards, model governance, and CI/CD best practices across the full machine learning operational lifecycle. Requirements Experience & Mindset Experience: Senior-level proficiency (10-20+ years) in software engineering, MLOps, production ML system deployment, and infrastructure scaling. Domain Adaptability: Demonstrated ability to deploy and maintain production ML systems across non-standard, highly specialized domains (e.g., transition between process/chemical engineering ML and clinical/scientific research applications). Location & Work Auth: Must hold unrestricted US Work Authorization (no sponsorship available) and be able to work 3 days per week onsite in the Indianapolis, IN area. Culture & Communication: Pragmatic problem-solving mindset, strong collaborative drive, and the ability to articulate complex MLOps architecture to cross-functional engineering teams. Must-Have Technical Stack Languages & Frameworks: Advanced Python, C++, and deep proficiency with PyTorch, TensorFlow, or Scikit-learn. MLOps & Serving: Proven expertise with Triton Inference Server, TorchServe, MLflow, Kubeflow, or Databricks ML runtime. Infrastructure & Orchestration: Hands-on expertise with Kubernetes, Docker, CI/CD pipelines, FastAPI/gRPC, and cloud platform ecosystems (AWS/Azure). Monitoring & Integration: Experience building real-time model monitoring, feature stores, drift detection systems, and integration with enterprise data pipelines. Domain Competency (Scientific & Process Focus) Deep exposure to applying ML models in either scientific/clinical domains (drug discovery, small/large molecule, computational biology) OR chemical/process engineering environments (API manufacturing, batch processing, SCADA/MES integration, process optimization). Nice-to-Haves & Certifications Academic background in Chemical Engineering, Bio-process Engineering, Computer Science, or a related STEM discipline. Direct experience operationalizing ML models inside regulated GxP environments in the Life Sciences or Specialty Chemicals sectors. Certifications: AWS Certified Machine Learning - Specialty, Databricks Certified Machine Learning Professional, or equivalent MLOps credentials. What This Role Is NOT Not a Data Scientist or Exploratory R&D Specialist: You will not be focusing on exploratory data analysis, academic algorithms, or standalone Jupyter notebook modeling; you are building, scaling, and maintaining production MLOps pipelines, inference engines, and model integration code. Not a non-coding Architect: This is a 100% hands-on MLOps and software engineering lead role requiring direct model deployment, infrastructure creation, and technical execution. Not a Fully Remote Position: This role requires a steady hybrid commitment of 3 days onsite per week at the client site in Indianapolis.

Job Description Job Description Senior .NET Engineer (multiple) U.S.-Based Applicants Only authorized to work for any employer (NO Sponsorship Provided) Referral Bonus Available - bring a friend! TeamBuilder is a rapidly growing healthcare SaaS company on a mission to modernize healthcare scheduling and workforce management. We are builders, executors, and big thinkers who want to solve real world problems. We win as one team. We're actively looking for multiple Senior .NET Engineers who want to take your engineering team to the next level. The ideal candidate thrives in a growing, tight-knit, fast paced environment and has experience scaling from zero to hundreds of thousands of users efficiently and cost effectively. Key personal attributes Quick study who can hit the ground running Strong critical thinker that can balance competing priorities Comfortable presenting, and pressure testing ideas You take pride in the quality and resiliency of your code - even when using AI You lead by example (not just by title) Equally committed to making your teammates successful (as yourself) Comfortable navigating uncertainty and trying new approaches You care as much about optimization, reliability and scalability as you do about building new things You like to ship working solutions with modern technology without overengineering Required skills/experience/qualifications Excellent written and verbal communication skills Experience working in teams with a mixture of onshore/offshore contributors A strong individual contributor but also able to effectively coach and unlock others Bachelor's degree in Computer Science, Software Engineering, or related field In-depth understanding of software engineering design and architectural patterns, including microservice architectures Adept at applying GenAI workflows to enhance your software development and testing efforts 8+ years' professional experience with .NET stack (C#, .NET, Entity Framework), SQL, and Redis 3+ years experience working with SignalR and Distributed Event Bus 3+ years' experience implementing Domain Driven Design (DDD) patterns 3+ years experience configuring and maintaining Microsoft Azure cloud services Advanced understanding of and ability to effectively use Git to manage code in a multi-developer environment Strong familiarity using and configuring CI/CD pipelines, ideally in Microsoft DevOps Nice to have You've come from a start-up that serves large enterprise clients Master's or other postgraduate degree Some exposure to machine learning / AI React / NextJS frontend skills Big data / analytics Principal duties and responsibilities Help drive technical excellence and standards within the team Develop well-written and documented code in both existing and new systems and platforms Support ongoing monitoring, maintenance and support of key infrastructure Design and apply manual tests and test-automation suites to minimize defects Provide sound recommendations on architectural choices leveraging significant prior experience and analysis of technical/business goals Develop well-written technical documentation to clarify requirements, improve code traceability, and enable cross-pollination of knowledge Apply good practice methodologies and techniques, such as story points, to quantify and estimate effort as accurately as possible Consistently attend sprint planning and stand-up calls to ensure alignment of priorities and effective troubleshooting support Proactively communicate feedback, issues, risks and status in a timely manner Assist in the training and development of other engineers Collaborate cross-functionally with product owners, data scientists, business users, project managers, and other engineers to achieve overall engineering and company goals effectively and in a timely manner Research and learn new technologies as needed to deliver technical solutions Actively participate in retrospectives of work done that assess code quality, system design, infrastructure, development processes, or client and consumer concerns Compensation / Benefits Powered by JazzHR azf7ADhdlq

Job Description Job Description Why Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection-between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you. About the Role Charlie Health leads the nation in high-acuity virtual behavioral care, having delivered life-saving treatment to more than 100,000 clients nationwide. Our ML and AI capabilities are expanding rapidly-powering recommendation systems, clinical decision support, agentic AI products, and developer tooling-and the infrastructure underneath needs to scale with them. As our first dedicated ML Platform Engineer, you'll define the technical direction and build the foundational systems that our data scientists, ML engineers, and product teams depend on to ship AI-powered features reliably and at scale. We have several models in production today and are investing in hosted GPU inference to support the next generation of our AI capabilities. You'll inherit and evolve existing infrastructure while building new platform capabilities-from multi-tenant model serving and GPU inference pipelines to multimodal data management, evaluation frameworks, observability, and infrastructure as code. You'll own the platform layer that makes ML/AI development at Charlie Health fast, safe, and repeatable as the team grows. If you care about building the systems that let others build great things, this team is for you. Responsibilities Infrastructure & Serving Define technical direction for ML/AI infrastructure and make build-vs-buy decisions as the founding platform engineer Design and operate multi-vendor AI infrastructure supporting client-facing and clinician-facing LLM applications across multiple LLM providers Design, build, and operate production model serving systems; maintain infrastructure as code for reproducible ML environments, training pipelines, and deployment workflows Develop high-performance GPU inference pipelines with low latency and high availability Own the multimodal data pipeline layer-manage ingestion, processing, and serving of text, audio, and structured clinical data for ML and AI systems AI Systems & Tooling Create reliable infrastructure for agentic AI systems, including orchestration, monitoring, evaluation, and observability tooling Build developer tooling that accelerates data science and ML engineering workflows across the organization Observability & Operations Own AI observability-build monitoring, alerting, and debugging capabilities for production ML systems Partner with ML engineers, data scientists, and product teams to understand infrastructure needs and translate them into scalable platform capabilities Foster a culture of collaboration and learning across engineering, product, and design through mentoring, documentation, presentations, and knowledge sharing Participate in our on-call rotation to ensure model serving uptime, pipeline reliability, and infrastructure health Requirements 4+ years of professional experience in software engineering, with at least 2 years focused on ML infrastructure, ML platform, or AI systems engineering Strong software engineering fundamentals in Python and deep infrastructure expertise Familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, or similar) and CI/CD for ML pipelines Experience with infrastructure as code (Terraform, Pulumi, or similar) and container orchestration (Kubernetes, ECS) Experience building evaluation and observability systems for LLM-based or agentic AI applications is a plus Excellent at managing ambiguity-able to break down big, messy problems into smaller parts with tractable solutions and clear iterations Growth mindset and sense of humor; you welcome feedback, adapt quickly in a fast-paced environment, and foster a culture of learning and fun Experience with a systems language (Go, Rust, or C++) is a plus This role requires 4 days per week in our NYC office (Flatiron District). The team is entirely based out of NYC. Benefits Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here. The total target base compensation for this role will be between $170,000-$220,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. Our Values Connection: Care deeply & inspire hope. Congruence: Stay curious & heed the evidence. Commitment: Act with urgency & don't give up. Please do not call our public clinical admissions line in regard to this or any other job posting. Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: -openings. Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent email addresses. Legitimate emails will never originate from or other commercial email services. Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals. At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people. Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation. By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service. By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.

Job Description Job Description Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health. By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare. What We're Looking For We're looking for a Senior Site Reliability Engineer to join our Data & ML Platform team. You'll be at the forefront of building and operating a resilient, observable, and scalable platform that enables mission-critical data and ML workloads across our organization. This role is ideal for someone who combines a strong SRE mindset with deep cloud infrastructure and data platform experience . You're comfortable operating at scale in a complex, hybrid cloud environment and can architect systems that balance velocity, safety, and cost. You'll work closely with Data & ML Engineers, Data Scientists, Analysts, and App Engineering teams to build a modern data platform that is secure, self-service, and production-grade. What You Will Do Operate and Improve Databricks and Snowflake : Own Databricks & Snowflake platforms lifecycle-including automation, workspace governance, job orchestration, and cost optimization. Design for Reliability : Architect resilient, scalable, and secure infrastructure across cloud environments. Drive initiatives around failover, autoscaling, chaos testing, and capacity planning. Advance Observability : Build and maintain platform-wide monitoring, alerting, and logging infrastructure using Datadog and other open tooling. Define and enforce SLOs/SLAs for critical services. Drive CI/CD for Data & ML : Automate deployments of data pipelines, ML workflows, and infra components using GitHub Actions , Terraform, and related IaC tooling. Enable Data Flow Across Platforms : Build patterns and tooling to support inter- and intra-cloud data movement across systems like Snowflake, S3, Delta Lake, and Kafka. Champion Event-Driven Architectures : Leverage cloud-native tools like EventBridge , SNS/SQS, and Lambda to build loosely coupled, scalable data systems. Collaborate Across Teams : Serve as the SRE and platform partner for teams across the organization, ensuring the platform meets the needs of analytics, data science, and product use cases. Contribute to Strategy : Influence engineering-wide decisions on data platform architecture , ML enablement , and data product strategy . What You Need to Succeed 6+ years in SRE, platform engineering, or DevOps roles supporting data-intensive or ML-powered applications. AI-native working style: daily use of Claude Code, Cursor, Copilot, or equivalent, with views on how they make a team faster. Hands-on Databricks experience , including workspace setup, cluster/job management, and integration with CI/CD and data orchestration tools. Experience with Snowflake as well. Deep understanding of cloud-native infrastructure on AWS (or similar), including VPCs, IAM, event-driven patterns, and serverless compute. Proven expertise with observability tools (especially Datadog) and architecting platform-wide logging and monitoring solutions. Strong command of CI/CD tooling , especially GitHub Actions , infrastructure-as-code (Terraform), and deployment automation for data systems. Working knowledge in shell scripting and Python. Experience building and supporting highly available, fault-tolerant systems . Excellent communication and collaboration skills; able to work effectively across teams. What Helps You Stand Out DevSecOps mindset : Familiarity with implementing security best practices in IaC, CI/CD, secret management, and audit logging. Experience with ML infrastructure tooling such as MLflow, Feature Stores, and GPU workload orchestration. Strong experience in both Databricks and Snowflake in a large scale production lakehouse with cross-warehouse interoperability, e.g. Iceberg v3, Glue, etc. Background in compliance-aware architecture (e.g., HIPAA, SOC 2) or regulated industries. Familiarity with multi-cloud or hybrid cloud data environments ; experience with Azure. Contributions to open-source infrastructure, SRE, or observability tools. We are committed to building a diverse team of Datavanters who are all responsible for stewarding a high-performance culture in which all Datavanters belong and thrive. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. At Datavant our total rewards strategy powers a high-growth, high-performance, health technology company that rewards our employees for transforming health care through creating industry-defining data logistics products and services. The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job. The estimated total cash compensation range for this role is: $168,000-$200,000 USD To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion. This job is not eligible for employment sponsorship. Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay. At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren't even able to see whether you've responded.) Responding is entirely optional and will not affect your application or hiring process in any way. Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the 'Interview Accommodation Request' category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis. For more information about how we collect and use your data, please review our Privacy Policy.

Job Description Job Description Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity. We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis. Our breakthrough DeepStain and ReStain technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities. About the Role We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor's virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows. Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges Explore image representation in latent space for efficient, high-fidelity virtual staining Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs' product roadmap Collaboration Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches Required Qualifications PhD (preferred) or Master's degree in Computer Science, Electrical Engineering, or a related field Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising Expert proficiency in Python and PyTorch and other scientific computing environments a plus Strong mathematical foundation in linear algebra, probability, and optimization Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure) Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles Experience with feature search, data balancing, and data curation pipelines. Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment Extensive use of AI tools for coding, optimization, and ideation Preferred Qualifications Experience with medical imaging, digital pathology, or whole slide image (WSI) processing Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem Background in generative models and fine-tuning of foundation models Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton Experience with hosting computer vision model inference on NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility What We Offer The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.

Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Secret What You Will Do: The Data Scientist will focus on performing ETL / data cleaning, developing interactive visualizations, building predictive models, and support implementing Artificial Intelligence solutions tied to asset and material maintenance and management data, as well as policy data. The data analyst will be responsible for all of the following to include but not limited to: Dedicated to workstream tasking and reports directly to the workstream lead Working closely with workstream lead in day-to-day execution of project tasks Collect, and analyze diverse data for creation of performance metrics and producing outputs to client What You Will Need: An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance. Bachelors Degree. THREE (3) or more years of specialized experience in data analysis. Python or R Programming experience Experience in at least one visualization tool (e.g. Tableau, Qlik, Power BI) Must be able to be on client site at least 3-4 days a week in the Tidewater area. What Would Be Nice To Have: Experience developing data pipelines and scripts using Databricks Experience developing in Palantir Foundry RPA or general automation experience in UiPath or Microsoft Power Automate Experience implementing military or industry business solutions and services Experience in understanding and applying data to develop reports, visualizations, and other deliverables Experience in analysis of statistical and mathematical modeling of data (i.e., regression analysis, simulation, impact analyses, geographic analyses, performance measurement/management) Experience with the Microsoft Power Platform (Power Apps, Power Automate, Power BI) (Desirable) Knowledge of Navy operations and data systems, in particular Naval supply and or maintenance What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Secret What You Will Do: The Data Scientist will focus on performing ETL / data cleaning, developing interactive visualizations, building predictive models, and support implementing Artificial Intelligence solutions tied to asset and material maintenance and management data, as well as policy data. The data analyst will be responsible for all of the following to include but not limited to: Dedicated to workstream tasking and reports directly to the workstream lead Working closely with workstream lead in day-to-day execution of project tasks Collect, and analyze diverse data for creation of performance metrics and producing outputs to client What You Will Need: An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance. Bachelors Degree. THREE (3) or more years of specialized experience in data analysis. Python or R Programming experience Experience in at least one visualization tool (e.g. Tableau, Qlik, Power BI) Must be able to be on client site at least 3-4 days a week in the Tidewater area. What Would Be Nice To Have: Experience developing data pipelines and scripts using Databricks Experience developing in Palantir Foundry RPA or general automation experience in UiPath or Microsoft Power Automate Experience implementing military or industry business solutions and services Experience in understanding and applying data to develop reports, visualizations, and other deliverables Experience in analysis of statistical and mathematical modeling of data (i.e., regression analysis, simulation, impact analyses, geographic analyses, performance measurement/management) Experience with the Microsoft Power Platform (Power Apps, Power Automate, Power BI) (Desirable) Knowledge of Navy operations and data systems, in particular Naval supply and or maintenance What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Duration: 12-Month Contract + Possible Extension Industry: Energy / Utilities Seeking an experienced Geospatial Data Engineer with strong expertise in AWS, PySpark, and large-scale geospatial data processing. The ideal candidate will have hands-on experience building cloud-native data pipelines that support geospatial analytics, remote sensing initiatives, asset management, and risk modeling programs. Position Summary The Geospatial Data Engineer will partner with cross-functional teams including Data Engineering, Data Science, GIS, and Solution Architecture to design, develop, and optimize scalable geospatial data solutions. This role focuses heavily on AWS-based data engineering, large-scale raster and satellite imagery processing, and the development of high-performance geospatial analytics pipelines. The successful candidate will play a key role in building and maintaining data platforms that integrate asset, environmental, operational, and geospatial datasets to support advanced analytics and business intelligence initiatives. Core Responsibilities Data Pipeline Engineering Design, develop, and maintain scalable AWS-native data pipelines using Python and PySpark. Build automated ingestion, transformation, and processing workflows for large geospatial and operational datasets. Optimize pipeline performance, scalability, and reliability. Remote Sensing & Raster Data Processing Develop and support data pipelines for large raster-based datasets and satellite imagery. Manage multi-band imagery, including visible, near-infrared, and red-edge spectral bands. Implement selective and incremental ingestion strategies to efficiently process only relevant data subsets. Cloud Data Architecture Design and maintain cloud-native geospatial data solutions within AWS. Support data lake, warehouse, and analytical platform initiatives. Geospatial Processing Develop distributed geospatial processing solutions using Apache Sedona, GeoPandas, Shapely, and related technologies. Perform large-scale spatial analysis, joins, indexing, and optimization. Data Platform Development Support modern data engineering practices including CI/CD, automated testing, version control, and Infrastructure as Code. Contribute to enterprise data governance and data quality initiatives. Agile Collaboration Work closely with Business Analysts, Product Owners, GIS Specialists, Data Scientists, and Engineering teams in an Agile environment. Participate in sprint planning, design reviews, and technical discussions. Required Qualifications Education Bachelor's degree in Computer Science, Engineering, GIS, Geography, Data Science, or a related field. Experience 7+ years of Data Engineering experience designing and supporting enterprise-scale data pipelines. Technical Requirements Strong proficiency with Python, PySpark, SQL, and Apache Sedona. Hands-on experience building geospatial and raster data processing solutions on AWS. Experience developing cloud-native ETL and data integration workflows. Strong understanding of coordinate reference systems, projections, and spatial transformations (WGS84, NAD83, EPSG standards). Geospatial Technologies Experience with Shapefile, GeoJSON, GeoParquet, GeoPackage, KML, GeoTIFF, and Cloud-Optimized GeoTIFF (COG). Experience processing large-scale raster datasets and satellite imagery. Expertise with raster-vector analysis and multi-band imagery processing. Understanding of vegetation, environmental, and remote sensing analytics workflows. Spatial Analytics Spatial indexing and partitioning techniques including R-Tree, QuadTree, and distributed spatial joins. Geometry operations including buffering, intersections, nearest-neighbor analysis, topology validation, and geometry simplification. Experience addressing performance optimization challenges for large spatial datasets. Data Engineering & Orchestration Experience with Airflow, Dagster orchestration platforms. Knowledge of dimensional modeling, historical data management, and data warehousing concepts. Familiarity with CI/CD practices, automated testing, and Git-based development workflows. Nice to Have Experience with Palantir Foundry. STAC or other satellite imagery cataloging standards. LiDAR datasets and processing workflows. Utility, energy, environmental, infrastructure, or asset management industry experience. Experience building geospatial machine learning or advanced analytics solutions.

Sr. Manager, AI Engineer (IFX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Manager, AI Engineer (IFX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 1 year of people leadership experience Preferred Qualifications: 3 years of experience managing and leading an engineering team 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance Track record mentoring engineers/scientists to productize prototypes and meet production SLOs Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Foundations) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.

CryptoAnalyzer, a leader in cryptocurrency analytics and blockchain solutions, seeks an RRT PRN Seasonal professional to support our finance and insurance analytics team during peak project cycles. In this role, you will review, reconcile, and test financial risk models, transaction reports, and trend dashboards related to digital assets. You'll collaborate with blockchain engineers and data scientists to validate datasets, flag anomalies, and document findings. This seasonal, as-needed position is ideal for detail-oriented analysts seeking hands-on exposure to cutting-edge crypto finance operations in a fast-paced, innovative environment. Responsibilities Support review and testing of cryptocurrency financial risk models and reports Reconcile data across multiple blockchain and market data sources Validate dashboards and transaction analytics for accuracy and completeness Identify and document anomalies, trends, and potential data quality issues Collaborate with data scientists and engineers on dataset improvements Prepare clear documentation for analysis methods and findings Assist with ad hoc queries and reporting for finance and insurance clients Follow internal controls and compliance guidelines for financial data Required Skills Financial data analysis Cryptocurrency and blockchain fundamentals Risk modeling support Data reconciliation and validation SQL or similar query languages Excel/Google Sheets (advanced) Dashboard and reporting tools (e.g., Power BI, Tableau) Statistical analysis basics Documentation and audit support Compliance awareness in finance/insurance