Clera

Job Description Job Description About the Role Join a Series A AI-powered engineering automation startup that is reimagining computer-aided engineering (CAE) for the AI era. As an AI/ML Engineer , you will shape the future of simulation and design automation by building AI that thinks like an engineer. You'll design, train, and deploy models that accelerate simulation, improve accuracy, and unlock new ways of exploring the design space - from adaptive solvers and reduced-order modeling to generative design and real-time validation. You'll work alongside experts in engineering and applied AI to integrate machine learning directly into high-fidelity simulation pipelines, helping customers iterate faster, diagnose failures earlier, and bring better products to market. This is an early, foundational opportunity with real impact at a fast-moving startup. Visa sponsorship is available for this role. What You'll Do Research, design, and develop AI/ML algorithms to tackle complex challenges in computer-aided engineering, simulation, and design automation. Build scalable AI solutions and collaborate with cross-functional teams to integrate models seamlessly into existing CAE workflows and infrastructure. Lead performance improvements - from optimizing model accuracy to analyzing outputs and addressing system-level bottlenecks. Guide AI/ML projects end-to-end, from research and prototyping through to scalable production deployment. Partner with engineering domain experts to develop physics-informed and geometry-aware ML approaches. What We're Looking For Required: 4+ years of experience developing and deploying AI/ML models with a proven track record of delivering impact in applied engineering or scientific domains. 2+ years of technical leadership guiding AI/ML projects from research to production. Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, JAX, TensorFlow). Experience with AI/ML algorithms for sequential, spatial, or physics-informed data (e.g., time series, mesh, or simulation outputs). Familiarity with MLOps practices and building AI/ML systems end-to-end, from prototyping to scalable deployment. Bachelor's or advanced degree in Computer Science, Mechanical Engineering, Electrical Engineering, or a related field. Strong problem-solving skills and attention to detail with demonstrated project success. Ability to work collaboratively with cross-functional teams and communicate technical concepts effectively. Nice to Have: Experience with computer-aided engineering (CAE), computer-aided design (CAD), and/or product lifecycle management (PLM) tools (e.g., ANSYS, SolidWorks, Abaqus, COMSOL, CREO, Autodesk Inventor). Experience in a fast-paced, early-stage startup environment. Familiarity with proficiency in C++ or Java in addition to Python. Understanding of engineering principles in simulation, modeling, and optimization. Compensation & Benefits Salary: $150,000 - $250,000 USD per year, depending on experience. Early-stage equity opportunity. Work alongside a team with backgrounds from leading national labs, research institutions, and top-tier technology companies. Location This role is based on-site in San Francisco, California, USA . The company is headquartered in San Francisco and prefers candidates who can work from the office.

Job Description Job Description About the Role We're a pre-seed AI-powered HR tech startup based in San Francisco, building the next generation of intelligent talent-matching products. Our core product team is small, fast-moving, and deeply technical - you'll work shoulder-to-shoulder with founders, product, and design to ship agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. We're looking for a mid-level AI Engineer (2-8 years of experience) who is comfortable owning production systems end-to-end, from data model to deploy and monitoring, and who thrives in an environment where pragmatic engineering judgment matters as much as technical depth. Visa sponsorship is not available for this role. What You'll Do Design, build, and maintain agentic systems that automate complex, multi-step workflows across domains such as healthcare, legal, fintech, logistics, and compliance. Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure - including vector databases, embeddings, and indexing - for domain-specific search at scale. Implement multi-agent orchestration , tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences. Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability. Ship full-stack AI products from MVP to enterprise-grade: design APIs and data models, implement frontend and backend code, and operate production systems with CI/CD, monitoring, and testing. Collaborate cross-functionally to prioritize work, define success metrics, and iterate based on user feedback and telemetry. What We're Looking For Must-haves: 2+ years of software engineering experience with a track record of shipping user-facing or backend products. Practical experience deploying LLMs or LLM-based services in production , including prompt design, orchestration, and tool integration. Full-stack proficiency: Python plus TypeScript/React (or equivalent), experience with cloud platforms ( AWS or GCP ), and relational or NoSQL databases. Working knowledge of RAG patterns , vector databases, embeddings, and retrieval pipelines, with sound judgment to choose appropriate approaches. Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos. Experience designing API-driven, high-throughput systems and real-time product features. Nice-to-haves: Experience with agent or workflow frameworks such as LangGraph or CrewAI , and orchestration tools such as Temporal or Trigger . Background building multi-tenant or enterprise-ready systems , or experience in regulated industries (healthcare, fintech, legal). Familiarity with fine-tuning, parameter-efficient tuning , or multi-modal model integration. Compensation & Benefits Salary: $180,000 - $400,000 USD annually (inclusive of equity where applicable) Early-stage equity opportunity High-ownership, high-impact role on a lean, experienced core team Location This is an on-site role based in San Francisco, CA . Candidates must be located in or willing to relocate to the San Francisco Bay Area. Visa sponsorship is not available.

Job Description Job Description About the Role This is a founding engineering role at a seed-stage AI startup building the intelligence layer for the construction industry. The company's platform transforms messy blueprints, permits, and construction documents into actionable insights - accelerating cost estimation and permitting workflows that directly impact housing, hospitals, and schools. As a Founding AI Engineer , you'll be one of the earliest technical hires, working hands-on with state-of-the-art computer vision, LLMs, and multimodal AI to prototype and ship production systems on real-world, noisy construction documents. The focus is squarely on the intelligence layer - modeling, data pipelines, and inference - not the application UI. This is a full-time, in-office role based in San Francisco, CA. Candidates must be based in SF or willing to relocate. US work authorization is required; visa sponsorship is not available. What You'll Do Apply state-of-the-art computer vision, LLM, and multimodal AI techniques to real-world construction documents (blueprints, schedules, specs). Rapidly prototype models and iterate based on user feedback and real production data. Build and deploy end-to-end AI systems that operate reliably on noisy, heterogeneous inputs. Own the intelligence layer: modeling, data pipelines, and inference infrastructure. Collaborate closely with product and users to surface and prioritize high-impact problems. Embrace practical engineering work - data labeling, ETL, deployment - as part of a small, high-trust team. Communicate progress, tradeoffs, and results clearly and empathetically across the team. What We're Looking For Must-haves: Demonstrated experience applying computer vision and/or multimodal AI in production - on real-world, messy data (documents, images, mixed modalities). 0-to-1 builder mindset : you've launched an AI system into production or built the core of a new product from scratch. Hands-on experience with LLMs and modern CV/multimodal model tooling and techniques. Comfort iterating quickly and improving prototypes directly from user feedback. Strong communication skills - honest, empathetic, and transparent with teammates and stakeholders. Willingness to handle the full spectrum of startup engineering tasks (no task is too small). Based in San Francisco or willing to relocate; US work authorization required. Nice-to-haves: Experience building something that shipped to real users or paying customers. Background or domain knowledge in construction, AEC (architecture/engineering/construction), or related industries. Experience at an early-stage startup or founding team environment. All experience levels are welcome, including recent graduates with strong production ML portfolios. Compensation & Benefits Salary: $120,000 - $180,000 per year, depending on experience Equity participation as a founding team member Opportunity to shape the technical direction of an AI product from the ground up Location San Francisco, CA - full-time in-office Relocation-ready candidates strongly encouraged to apply US work authorization required; visa sponsorship is not available

Job Description Job Description About the Role A growing AI and Data Science team at a healthcare-focused company is looking for a Senior Machine Learning Engineer to take ownership of complex, enterprise-scale ML initiatives. This is a W2 contract role for work-authorized candidates (no visa sponsorship available). You'll work in a fast-paced environment building production-grade ML solutions that directly impact patient outcomes and healthcare operations - with a strong emphasis on compliance, reliability, and end-to-end ownership. Ideal candidates bring 8+ years of professional ML engineering experience and a mandatory background in the healthcare industry , including hands-on experience with HIPAA-compliant systems and sensitive patient data. What You'll Do Own the full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, monitoring, retraining, and maintenance. Design and build scalable, production-ready ML systems with high availability, performance, and reliability. Develop and maintain MLOps pipelines - including CI/CD, model registry, feature stores, automated deployment, monitoring, and rollback strategies. Monitor production models for drift (model, data, accuracy degradation) and overall system health. Build and integrate REST APIs to connect ML services into enterprise cloud applications. Optimize models for latency, scalability, reliability, and operational cost. Provide technical leadership on AI/ML initiatives across the organization. Collaborate with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business stakeholders. Ensure strict compliance with HIPAA, PHI, PII, and enterprise security standards throughout all ML workflows. What We're Looking For Required - Dealbreakers: 8+ years of professional software engineering and machine learning experience. Healthcare domain experience is mandatory - including HIPAA compliance and handling of sensitive patient data (PHI/PII). Demonstrated ownership of end-to-end ML lifecycle from data preparation through deployment, monitoring, and retraining. Experience designing and operating production-grade ML systems at scale. Hands-on MLOps: CI/CD pipelines, model registry, feature stores, automated deployment, monitoring, and rollback. Required Technical Skills: Languages: Python, SQL Platforms: Databricks (production), Apache Spark (distributed computing), MLflow, Feature Store, Model Registry Cloud: Azure, AWS, and/or GCP for ML workloads Infrastructure: Docker, Kubernetes, REST APIs, Git, CI/CD pipelines Strong debugging and performance-tuning skills; excellent stakeholder communication. Nice to Have: LLMs in production, prompt engineering, RAG, and/or GenAI applications Scala Azure ML, SageMaker, or Vertex AI Distributed ML architecture design HIPAA-compliant AI solution design experience Compensation & Details Rate: $70-75/hr on W2 (equivalent to $145,600-$156,000 annualized) Type: W2 Contract Visa sponsorship: Not available - open to all work-authorized candidates Location Primary location: San Francisco, CA . Additional locations considered include Los Angeles, CA and New York City, NY. Remote-friendly role.

Job Description Job Description About the role Our client is a well-funded AI startup building production-grade ML infrastructure used by enterprise customers. They are looking for a Senior AI/ML Engineer to own model training pipelines, evaluation systems, and inference serving at scale. Full-time, on-site in San Francisco. What you will do Design and ship end-to-end ML systems: data pipelines, training, evaluation, deployment Own model performance, latency, and cost trade-offs in production Build evaluation harnesses and offline benchmarks for fast iteration Work directly with product to translate ambiguous goals into measurable model improvements Mentor other engineers on ML best practices and code quality What we are looking for 4+ years of applied ML engineering in production environments Hands-on experience with LLMs, fine-tuning, RAG, or large-scale recommender systems Strong Python and PyTorch (or JAX) fundamentals Experience with distributed training, GPU optimization, or inference serving Pragmatic about trade-offs between research-grade and ship-grade work This role is presented by a recruiting partner. Company name shared after an initial conversation.

Job Description Job Description About the Role A fast-growing, Y Combinator-backed B2B SaaS startup in the sales automation space is looking for an AI/LLM Engineer to join their team in Munich. The company automates quote and order processing for distributors and manufacturers - helping sales teams eliminate manual overhead and close more deals with AI-driven tooling. This is a high-impact, full-stack AI engineering role where you'll own end-to-end delivery of intelligent features: from data pipelines and LLM fine-tuning to production deployment. You'll be joining a small, senior team at an early stage with significant engineering ownership and direct influence on product direction. What You'll Do Design, build, deploy, and optimize AI agents across the full stack - end to end Work with embeddings and fine-tune LLMs for classification and reranking tasks Optimize algorithms for product search and matching Apply RLHF and DPO techniques to align LLMs with human feedback Build robust data pipelines to process large-scale unstructured data efficiently Contribute to backend scalability, stability, and performance improvements What We're Looking For Must-haves: 2+ years of hands-on engineering experience Strong experience with NLP, LLMs, embeddings, ML, and production AI agents Experience with full-stack development using React, TypeScript, and Next.js Demonstrated experience scaling data and ML pipelines, including large-scale unstructured data Practical experience with RLHF and DPO for LLM alignment Strong CS fundamentals Willingness to work on-site in Munich Nice to have: Experience with containerization ( Docker, Kubernetes ) Cloud infrastructure experience (AWS, Azure, or GCP) Infrastructure-as-code experience ( Terraform ) Compensation & Benefits Salary: $90,000 - $200,000 USD annually (depending on experience) Visa sponsorship available Early-stage equity opportunity at a well-funded, high-growth startup Location Munich, Germany - on-site role Visa sponsorship is available for the right candidate