Machine Learning Jobs in Berkeley, CA

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Develop software for clinical brain-computer interface applications, including BCI data curation, neural decoding algorithms, hardware-in-the-loop evaluation, and software tools. Collaborate with scientists, engineers, neuroscience, machine learning, and quality teams to define requirements, review code, and support clinical studies. Regular travel between Austin and Oakland offices is required.

Build and maintain scalable, reliable ML data platform systems to support dataset generation, model training, analytics, monitoring, and large-scale inference. Collaborate with ML, software, and infrastructure engineers to design cost-efficient data lake and training infrastructure using vendor and open-source tools to enable next-generation ML models.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

The Machine Learning Scientist will develop reinforcement learning algorithms for protein design, collaborate with teams, and shape machine learning strategies.

The Senior Manager, Product Lead will oversee a team of product managers, driving product strategy, talent development, and excellence in AI-powered legal products.

Lead and scale a multidisciplinary software organization spanning autonomous robotic vehicles, web-based solar plant tools, and AI agents. Own software architecture, roadmap, product delivery, hiring, and engineering leadership. Guide robotics fleet software, telemetry and data infrastructure, AI systems, cloud and edge platforms, and design, build, and operations products. Partner with hardware, commercial, and project operations teams to deliver reliable software supporting rapid growth.

Build reliable machine learning and data systems that transform assay videos, scientific data, and experimental outcomes into reproducible models, evaluated predictions, and experiment recommendations. Responsibilities include data and feature pipelines, model training and evaluation infrastructure, batch and online inference systems, monitoring, data quality, versioning, observability, and interfaces across computer vision, molecular modeling, active learning, and laboratory workflows.

Conduct research on machine-learning methods that recommend informative scientific experiments. Develop multimodal models using molecular, assay, behavioral, and laboratory data; create active-learning and sequential experiment-selection methods; design evaluations robust to distribution shift; investigate generalizable behavioral signals; and translate model failures into improved experiments, labels, and controls. Communicate findings clearly to experimental scientists and validate models prospectively.

Lead the Platform Software Engineering team building and scaling core data infrastructure for research, market-making, and risk platforms. Hands-on role combining individual contributor work, system architecture, cross-functional project leadership, and people management while collaborating with Research and Business Operations.

The Forward Deployed Research Scientist engages directly with AI labs to develop data strategies, fine-tune models, run experiments, and collaborate on publishing research, all in a fast-paced client-focused setting.

Build and maintain backend APIs and data pipelines that ingest and process large-scale construction data (360° video, schedules, IoT). Optimize storage and query performance using DuckDB and PostgreSQL, extend Airflow workflows, integrate Wasm for local computation, monitor data quality, and collaborate with frontend, CV, and ML teams to deploy production models and analytics.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Build large-scale machine learning systems for advertising, including ranking, recommendation, targeting, prediction, optimization, and creative generation. Develop feedback loops connecting generative AI outputs to advertising performance signals, apply prompt engineering and post-training methods, run experiments, and ship reliable production ML systems. Collaborate across Product, Research, Engineering, and go-to-market teams to deliver AI-native advertising products.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

The Software Engineer, Perception develops autonomous aircraft systems to detect and manage wildfires using real-time data processing and machine learning techniques.

Senior pre-sales engineer partnering with sales and channel partners to run technical demos, lead POCs, design solutions, and close large deals. Present to executives and technical audiences, build cloud ML/generative AI solutions, and advise on data architecture and Snowflake positioning.

As an ML research engineer, you will develop systems using language models, curate datasets, set evaluation metrics, and scale semantic search processes.

Develop data-analysis pipelines bridging ultrasound, synthetic biology, imaging and sequencing. Collaborate with wet-lab and ML teams to define objectives, encode priors, run ML pipelines for de-novo design and closed-loop active learning, and produce actionable insights to accelerate molecule discovery and device optimization.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

As an Automation Engineer, you'll build automation pipelines, collaborate on experimental needs, program instrumentation, and integrate with data science, enhancing research capabilities.

As a Social Media Intern at Inception, you will manage social content across platforms, engage with AI discussions, participate in product launches, and create engaging video content. Aimed at students with a passion for AI and strong writing skills, the role offers direct access to the founding team and the potential for full-time conversion.

The Senior B2B Marketer will develop and execute marketing strategies, collaborate with Sales, create marketing materials, conduct research, and optimize marketing effectiveness to drive growth in the gaming and 3D industries.

Lead and grow a product-oriented software engineering team to design, own, and deliver Fervo's internal application architecture and production apps. Work embedded with operations to build workflows, dashboards, integrations, and AI-enabled features; define standards (CI/CD, observability, security); and manage vendor and data-platform integrations to scale software supporting geothermal operations.

The Machine Learning Scientist will lead open-source research, design experiments, develop novel methodologies, and analyze large-scale data to advance AI model evaluation and transparency.