55 jobs found

Job Description Job Description Job Description Technical Team Lead - Business Intelligence Platform Columbia, MD Full Time TS/SCI with Polygraph Required Position: Technical Team Lead (Software Engineer, Level 3) Location: Columbia, MD (on-site) Category: Software Engineering / Technical Leadership / Data Engineering Clearance Requirement: Active TS/SCI with Polygraph Compensation: $200,000 - $250,000 (annualized USD) Experience Requirement: 12+ years with a Bachelor's degree, OR 10+ years with a Master's degree, OR 4 additional years of relevant experience in lieu of a degree Description Serve as the Technical Team Lead for the Mission Intelligence (MI) team, supporting data engineering, analytics, and automation initiatives. The MI team operates a business intelligence platform that enables enterprise-wide, data-driven decision-making. Your primary responsibility is to ensure the reliability, availability, and quality of this high-impact platform. You'll also contribute to the MI team as a systems engineer, software engineer, and analytic developer - designing, developing, and integrating solutions that involve the analysis of large data sets to establish operational visibility and deliver actionable insights. Responsibilities Develop analytics to combine, normalize, and enrich large data sets. Design and implement ETL workflows to convert and normalize data. Augment the platform with new tools or technologies. Gather stakeholder requirements, assess available data, and develop solutions for delivering key metrics. Break down tasks into actionable steps that demonstrate consistent progress. Remove technical obstacles, manage expectations, and support team execution. Define and communicate task scope through clear documentation and tracking systems. Enable the team to integrate Site Reliability Engineering practices into the operational platform. Mentor and guide junior software engineers and data scientists. Produce project management materials such as agendas, meeting notes, and design decision records. Skills Requirements Experience supporting enterprise-scale platforms. Strong Java development skills. Familiarity with authentication and authorization platforms and standards. Experience with service containerization and deployment with Docker/Kubernetes. Familiarity with Git for software version control. Experience with Atlassian Tools (Jira, Confluence). Customer-service mindset. Experience leading technical teams. Effective interpersonal skills for collaborating across diverse backgrounds and skill sets. Experience or exposure to Site Reliability Engineering (SRE) principles. Willingness to contribute to internal and customer-facing documentation. Nice to Haves Experience with Apache NiFi. Experience with Elasticsearch and Kibana. Familiarity with Kubernetes. Knowledge of map-reduce analytic environments (e.g., Hadoop). Python experience. Prior experience in cyber operations or capability development. Compensation Employment Policy Salary is determined by multiple factors, including location, education, experience, skills, and organizational requirements. The projected compensation range for this position is $200,000 - $250,000 (annualized USD). Benefits Overview At Intezra, Inc., we offer a comprehensive benefits package designed to support long-term career growth and work-life balance: Three CareFirst medical plans available; Intezra pays up to 100% of healthcare premiums and up to 100% of deductibles (based on plan selection) for employees and dependents Intezra pays 100% for CareFirst Dental and Vision plans for employees and dependents 401(k): 15% company contribution (no match required) PTO: 160 hours, increasing with seniority 12 Floating Holidays 4 Code Red Days EEO Statement Intezra, Inc. provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, pregnancy, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. About Us Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years. , About Intezra, Inc. Intezra Inc. is a small business prime contractor for all realms of cyber and AI/ML development, from tactical-level tools and capabilities to enterprise-level infrastructure and operations. Our leadership team and staff have helped solve the most complex challenges for the intelligence community for over 15 years.

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 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 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.

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.

Senior Data Scientist Location: Woodlawn, MD Job Type: Long-Term Contract Work Arrangement: Onsite Interview: Video Interview Duration: Long Term Job Overview We are seeking an experienced Senior Data Scientist to join our team in Woodlawn, MD . The ideal candidate will have strong hands-on experience in Natural Language Processing (NLP), text processing, information extraction, Python, SQL, and data matching/entity resolution . This role will focus on developing advanced data processing solutions, building scalable data pipelines, improving data quality, and implementing techniques to identify and match records across large and complex datasets. Key Responsibilities Design, develop, and maintain advanced data processing and entity resolution pipelines using Python and SQL. Process, clean, transform, and manage large-scale datasets from multiple sources. Apply NLP, text processing, and information extraction techniques to structured and unstructured data. Implement data matching techniques such as Named Entity Recognition (NER), blocking and indexing, string similarity/distance metrics, TF-IDF, cosine similarity, phonetic matching, and address standardization . Develop data cleansing and validation solutions using Python and Regex. Write and optimize complex SQL queries and database operations for performance and scalability. Perform data validation, testing, deployment, and production monitoring. Participate in code reviews and follow version control, data security, reproducibility, and software development best practices. Collaborate with technical teams and business stakeholders to understand requirements and translate complex data-processing logic into practical solutions. Troubleshoot data quality and pipeline issues and implement reliable, scalable solutions. Required Qualifications Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, Information Science , or a related field. 10+ years of IT experience . Strong hands-on experience with Python and SQL . Strong practical experience with NLP, text processing, and information extraction . Experience with Named Entity Recognition (NER) . Experience with entity resolution, record linkage, data matching, or deduplication . Knowledge of blocking/indexing and string distance metrics . Experience with TF-IDF and cosine similarity . Experience with Regex for text processing and data cleansing. Knowledge of address standardization and phonetic encoding . Strong analytical, problem-solving, written, and verbal communication skills. Preferred Skills Experience with one or more of the following is highly desirable: spaCy Scikit-learn Splink Dedupe FastLink recordlinkage PostgreSQL DB2 Oracle SQL Server Hadoop Jenkins CI/CD Apache Airflow or other pipeline automation tools Preferred Experience Experience working on federal, state, or local government projects . Experience working with large-scale, legacy, or distributed data systems. Experience migrating and integrating data from multiple enterprise sources. Experience designing automated data-quality and validation pipelines. Ability to explain complex data-matching algorithms and business rules to technical and non-technical stakeholders. Ability to independently own projects from data discovery through development, deployment, and post-production support .

Headquartered in San Diego, Mulligan Funding serves as a leading provider of working capital (Up to $5M) to the small and medium-sized businesses that fuel our country. Since 2008, we have prided ourselves on our collaborative, innovative, and customer-focused approach. Enjoying a period of unprecedented growth, driven by the combination of cutting-edge technology, human touch, and unwavering integrity, we are looking to add to our people first culture, with highly motivated and results-oriented professionals, to push the limits of what's possible while creating value for all of our partners. Mulligan is modernizing small business lending by replacing manual processes with faster, smarter AI decisioning. With 18 years of proprietary credit data and deep domain expertise, we have both the institutional knowledge and the technical infrastructure required to make this vision a reality. We have already deployed production-grade AI agents in our core credit and underwriting workflows, delivering clear improvements in speed, accuracy, and consistency. We are now accelerating this effort across the rest of the business, bringing the same AI rigor to Sales, Customer Lifecycle, Finance, and Capital Markets while building an enterprise-grade product capability that scales. The Chief Credit Officer serves as the Executive Lead for Mulligan's AI strategy, setting the vision and holding final product and engineering design authority. We are seeking an AI Product Director to act as the CCO's senior strategic partner. In this role, you will help co-design product blueprints, translate strategic goals into precise technical specifications, lead delivery teams, manage external engineering partners, and partner closely with internal data teams. You will oversee day-to-day product authority, technical execution, and operational delivery across all concurrent AI projects. Reporting directly to the CCO, this role offers high executive visibility and is structured to grow in scope as our AI capabilities mature. Strategic Co-Design & Blueprint Authorship Co-Authoring Specifications: Partner closely with the CCO to translate strategic business objectives into detailed, buildable product and engineering blueprints for new AI initiatives. Regulatory & Compliance Integration: Ensure all AI design briefs explicitly account for relevant financial regulations (e.g., FCRA, ECOA / Regulation B, Fair Lending, Adverse Action rules) and model explainability standards prior to engineering builds. Process Intelligence Extraction: Conduct deep-dive discovery with Subject Matter Experts (SMEs) to map current processes and reimagine them through AI workflows - rather than simply digitising existing manual tasks. Execution Leadership & Enterprise Alignment Product Authority: Serve as the day-to-day product authority across active initiatives - leading working sessions, maintaining delivery velocity, and, within approved design frameworks, making the technical trade-off decisions that keep execution moving. Cross-Functional Orchestration: Lead interdisciplinary teams comprising Data Science pods, internal Data Engineering and IT infrastructure leads, and functional business partners to ensure clean data pipelines and scalable infrastructure for AI models. PM Team Development: Build, coach, and manage a high-performing team of Junior AI PMs - establishing review standards for process mapping and design briefs before final executive sign-off. Engineering Partner & Vendor Governance Technical Interface: Act as the primary product interface for external specialist engineering vendors. Evaluate architecture proposals and technical deliverables against Mulligan's specifications to ensure alignment. Vendor Principles: Enforce Mulligan's core partnership mandate: Mulligan authors the specification; partners never operate as unmonitored black boxes. Acceptance & Quality Criteria: Establish rigorous, verifiable acceptance metrics and output tests required for vendor milestone sign-off. Quality Control & Evaluation Framework Ownership Pre-Build QC Design: Define robust Quality Control (QC) frameworks - including human-in-the-loop (HITL) workflows, deterministic rule checks, and LLM-as-judge evaluation frameworks - during Phase 1 discovery, before engineering builds begin. Benchmarking: Collaborate with Data Science leads to establish baseline evaluation rubrics, golden datasets, and accuracy thresholds prior to end-user rollout. Stakeholder Engagement & Change Management Cross-Functional Sponsorship: Build trust across Sales, Credit, Operations, and Finance to ensure high end-user adoption and minimal operational disruption. Executive Visibility: Communicate clear programme metrics, delivery risks, and strategic trade-offs to key business leaders and executive management. Required Experience & Education 8-12 years in product management, with a demonstrated track record of taking AI-enabled solutions from concept to production deployment - in environments where execution speed and design quality both mattered. Prior experience contributing to the design of AI solutions - not just managing their delivery. Candidates who have been in the architecture room, not just the delivery room, will thrive in this role. Strong executive presence - demonstrated ability to lead cross-functional meetings with functional heads and senior stakeholders, hold the room with authority, and represent product direction credibly without senior sponsorship present. Prior experience in fintech, lending, or a credit-adjacent product environment is strongly preferred. Candidates from large-company product management backgrounds without fintech or high-velocity product experience are unlikely to succeed in this role. Demonstrated ability to extract precise current state process intelligence from domain SMEs and translate it into AI transformation design briefs that reimagine the process rather than digitise the status quo. Experience managing specialist external engineering partners through a full build cycle - including reviewing technical deliverables against a product specification and holding partners accountable to defined acceptance criteria. Proven ability to coordinate multiple concurrent AI initiatives simultaneously without losing execution quality, design fidelity, or stakeholder confidence on any of them. Bachelor's Degree in Business, Computer Science, Engineering, Economics, or a related technical discipline is required. Master's degree is a plus, but evaluated secondary to a strong, verifiable track record of shipping production AI products in fintech. Functional & Technical Skills Practitioner-Level AI Fluency: Deep familiarity with modern LLM architecture, agentic orchestration patterns, confidence-based decision routing, hallucination mitigation techniques, and golden dataset benchmarking - sufficient to co-author engineering blueprints, evaluate the soundness of partner-proposed architectures, and identify design gaps before they become build problems. Compliance & Model Governance: Working knowledge of credit regulations (FCRA, ECOA, Reg B), auditability requirements, and model governance in regulated industries. Process Discovery & Intelligence Extraction: Exceptional ability to interview domain experts, uncover undocumented edge cases, and translate current state intelligence into AI transformation design briefs that reimagine rather than digitize. Vision and ability to think outside of the box is mandatory Cross-Functional Communication & Executive Presence: The ability to lead rooms of functional heads, engineers, and data scientists with confidence and authority - holding the room credibly and driving decisions without senior sponsorship present. The ability to manage resistance to change from end-user communities without losing their trust. The ability to maintain executive confidence through honest, structured communication of programme health, risks, and trade-offs. This is a core competency of the role - not a background skill - and will be assessed directly in the interview process. $250,000 - $350,000 a year A reasonable estimate of the base compensation range for this role is $250,000 to $350,000 per year. Total compensation may include base salary and other forms of compensation, such as an annual bonus as applicable. In determining compensation, Mulligan Funding considers a variety of factors, including but not limited to market data, relevant experience, skills, education, and certifications. Mulligan Funding is an Equal Opportunity Employer (EOE) and takes great pride in building a diverse work environment. Qualified applicants are considered for employment without regard to age, race, religion, gender, national origin, sexual orientation, disability or veteran status.

Karman is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. The Power Applications team takes power control and orchestration algorithms from idea to production. We own the complete end-to-end process: developing power control and orchestration algorithms, translating them into deployable applications, and owning the deployment and maintenance of those applications in the field. As the Technical Lead, Power Applications, you will coordinate data scientists and software engineers to produce these applications, define repeatable and scalable workflows that let the team deliver efficiently, and act as the technical interface to other teams on the stack. This is a leadership role. While you will still spend meaningful time in the codebase, a large part of the work is communication, coordination, and project management. Your leverage comes from the designs you set, the standards you hold, the engineers you develop, and your ability to keep cross-functional work moving. Success in this role is measured by driving continuous delivery, building for scale and resilience, and navigating the demands of a rapidly growing company. This position works cross-functionally with product, engineering, and data science teams and is open to fully remote candidates, with periodic travel expected for company retreats and key on-site engagements. Responsibilities Enable the Power Applications team to own the end-to-end lifecycle of Utilidata's power control and orchestration applications, from algorithm development, through translation into deployable software, to deployment and ongoing maintenance in production Directly contribute to the Power Applications codebase and work with the team to define and own code quality standards and engineering workflows Serve as the senior individual contributor coordinating data scientists and software engineers, aligning the group on design and quality through architecture and code review Design continuous delivery workflows that bridge algorithm development and production, including the path from prototype code (e.g., Python) to the deployed application's language (e.g., Rust), so work moves to production smoothly and repeatably Act as the technical interface between Power Applications and other teams on the stack, establishing clear system boundaries, data contracts, and power application SLAs Contribute to system architecture discussions for the Karman platform as a whole, ensuring the subsystems that support power-flow control fit coherently into that wider architecture Build for reliability and scale so power applications run continuously across experimentation, staging, and deployed environments. Minimum Qualifications 10+ years of software engineering experience, including a track record of technical leadership on complex production systems Demonstrated ability to lead engineers through architecture, code review, and mentorship, and to raise the technical bar of a team Excellent written and verbal communication skills, with substantial experience working directly with stakeholders across teams Strong project management and technical planning skills - sequencing work, managing cross-team dependencies, translating product requirements into technical designs Strong foundation in distributed systems and reliability engineering: fault tolerance, graceful degradation, observability, and testing for systems that cannot go down Experience taking software from prototype to hardened production, ideally where the platform and requirements were still evolving Proficiency in Python and at least one systems language (C++, Rust, or Go) Willingness to travel up to 10% of time Enhanced Qualifications (Nice to Have) Hands-on experience with real-time, low-latency, or control systems : software that must respond within strict time bounds and behave predictably under load Experience with edge or embedded computing, especially on NVIDIA platforms (Jetson-class devices, CUDA, or NVML) Background in power systems, energy, industrial control, robotics, or another physical-world real-time domain) Experience productionizing ML models or algorithms in collaboration with data science teams Salary Range: $180,000 to $220,000 base compensation depending on experience and level, plus stock options. This role spans multiple job levels; final level and compensation will be determined based on the candidate's experience. Location: This position can be performed remotely from anywhere in the United States. Our Commitments: Karman values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws. We are committed to: Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful Empowering employees to solve problems and work together to make a difference Providing mentorship and growth opportunities as part of a collaborative team A flexible work environment with flexible paid time off Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping work on top priorities for the company. The Data team also functions as an in-house, production "customer" that dog foods Databricks and drives the future direction of the products. The impact you will have: " Analysis at the speed of thought ": Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists. " Extend capabilities of Databricks ": Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product " Strategic business insights ": Lead insight generation for top company priorities, and key Engineering initiatives (reliability, and efficiency). Gather changing requirements, define project OKRs and milestones, and communicate progress and results to both technical and non-technical audiences. Mentor and guide junior data scientists on the team by helping with project planning, technical decisions, and code and document review. Represent the data science discipline throughout the organization, having a powerful voice to make us more data-driven. Represent Databricks at academic and industrial conferences & events. What we look for: 7+ years of data science, machine learning, advanced analytics experience in high velocity, high-growth companies Extensive experience in applying Data Science / ML in production to build data-driven products for solving business problems. Experience collaborating with and understanding the needs of Senior level stakeholders from a variety of functions including: Engineering, Product, and Technical Operations. Ability to deal with ambiguity in fast paced environments by clarifying requirements and having a keen sense of 0 to 1 solutions. Adept at operating both as an individual contributor and identifying how to orchestrate the build through peers and investments in scalable tooling. Strong coding skills in Python and SQL Experience with distributed data processing systems like Spark and familiarity with software engineering principles around testing, code reviews and deployment. M.S. or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering) Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $192,000-$260,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

RDQ126R47 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Databricks Unity Catalog is the industry's only unified and open governance solution for data and AI, built into the Databricks Data Intelligence Platform. It enables data scientists, analysts, and engineers to securely discover, access, and collaborate on trusted data and AI assets across platforms. Unity Catalog enhances productivity through AI-powered governance, simplifying compliance while maximizing interoperability. We are seeking a Senior Staff Software Engineer to lead the technical direction and development of Unity Catalog's enterprise-grade governance capabilities. In this role, you will drive the roadmap and execution of critical features that empower organizations to govern access to their Lakehouse assets at scale. Key Responsibilities Technical Leadership : Lead the design and delivery of high-impact projects, setting standards for security, usability, performance, and scalability. Mentor senior engineers and elevate development and operational best practices across the organization. Product Ownership: Take full ownership of the Unity Catalog Governance product, driving it from initial concept to robust, scalable solutions with measurable business impact. Cross-Functional Influence: Collaborate with product and infrastructure teams to align technical strategy and execution, ensuring seamless integration and adoption of governance features. Operational Excellence: Champion the development of high-quality, reliable, and easy-to-operate software. Drive operational processes that deliver a seamless customer experience that is indistinguishable from perfect. What We Look For 15+ years of industry experience building and operating large-scale distributed systems. Proven track record of driving initiatives focused on customer satisfaction and incremental delivery. Deep computer science expertise (algorithms, data structures) with real-world application. Strong leadership, communication, and cross-functional collaboration skills. BS in Computer Science or related fields (MS/PhD preferred) (Preferred) Experience in data governance, security, privacy, identity management, authentication, or access control. Why Join Us? Influence the direction of industry-leading data and AI governance solutions. Work with world-class engineers and thought leaders in a collaborative, high-impact environment. Competitive compensation, comprehensive benefits, and opportunities for professional growth. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $217,000-$312,200 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

P-78 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure - with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We're building the infrastructure that powers the next generation of AI. The impact you will have Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly. Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail, etc. Interact with turnkey customers and product managers to envision new features and identify areas for improvement. Shape how developers and data scientists build and interact with AI on Databricks. What we look for 5+ years of experience in backend or infrastructure engineering with a focus on building systems Strong programming skills in Python, Scala or Java Experience with distributed systems, scalable APIs, or cloud-native infrastructure Familiarity with service-oriented architecture, deployment pipelines, and system observability Strong product and ownership mindset - you care about building the right solution, not just any solution Strong understanding of dependency management technologies including virtual environments or containerization technologies. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $166,000-$220,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

AI Engineer 4 (AI Foundations, VLM Customization) 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 McLean, VA: $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 Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Public Trust What You Will Do: The Border Security Data Scientist will join a dynamic team supporting U.S Federal border security customers. In this role, the candidate will collect, transform, integrate, and analyze data to. develop integrated data models, generate reports and analyses for key senior leaders and deploy dynamic analytical solutions. Develop integrated data pipelines and models to support law enforcement operations Develop and maintain data governance documentation, tools, and templates. Coordinate with non-technical users to gather requirements. Request, document, report, and analyze data, and where applicable, create tools and resources to support data and reporting. Support key mission clients within the Washington DC Metro region at client sites. We are actively hiring for this role at multiple levels (Associate, Senior, and Lead) to support ongoing and upcoming federal client work across CBP. Candidates will be considered and leveled based on experience, technical capabilities, and overall alignment to project needs. What You Will Need: An ACTIVE and MAINTAINED CBP PUBLIC TRUST or An ACTIVE and MAINTAINED "TOP SECRET" Federal or DoD security clearance. Bachelors Degree Experience in performing data analysis, mining and/or architecture using tools such as SQL, Python, R, etc. Experience developing transformative data integration solutions that transform border, national security or law enforcement data Experience performing modelling and/or simulation analysis What Would Be Nice To Have: Proficiency in querying and mining large classified data sets Proficiency in data wrangling and analysis using Python. Proficiency with COTS tools such as DataRobot, Senzing and others Experience developing bespoke analytical tools for law enforcement analysis Direct Experience supporting the National Targeting Center or similar National Security analysis fusion centers 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.