Machine Learning Jobs in Berkeley, CA

Conduct original philosophical and AI-alignment research, identify important research questions, connect conceptual analysis with empirical and technical work, design experiments and evaluations, collaborate across disciplines, and communicate findings through papers, reports, presentations, and external engagement. Depending on seniority, the role may also define research areas, shape the agenda, lead collaborations, and mentor researchers.

Consultative Sales Engineer responsible for driving complex sales opportunities, designing cloud data security and data risk management solutions, delivering proof-of-value engagements and technical demonstrations, advising executive stakeholders, supporting partner channels, and coordinating cross-functional resources. The role requires cloud security, IAM, networking, databases, encryption, privacy, data governance, and strong technical communication skills.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Write and edit accessible journalism about AI for a general audience. Responsibilities include pitching ideas, drafting articles, editing researchers’ and writers’ work, setting editorial standards, and helping launch a consistent media program. The founding editor will shape editorial direction and clarify technical material without oversimplifying it.

Design control-system requirements and architecture for a DNA-origami electrostatic actuator-sensor system. Define sensor and actuator constraints, review FET and drive-stack designs, specify experimental data capture for system identification and machine learning, and develop a closed-loop control, simulation, and estimation plan. Provide a documented handoff to the incoming Controls engineer while advising physics and wet-lab teams on a fractional contract basis.

Build and operate production MLOps infrastructure spanning experimentation, model training, deployment, serving, monitoring, retraining, and rollback. Develop ML data and feature pipelines using multimodal manufacturing data, maintain lakehouse and feature-store capabilities, and establish observability and human-in-the-loop feedback systems. Collaborate with data, AI, software, process, materials, and simulation engineers to deliver reliable, scalable ML platforms and model feedback loops.

Own and improve 2D, 3D, and fusion-based image segmentation models for clinical ultrasound and CT analysis. Build training, evaluation, dataset, and labeling pipelines; collaborate with clinicians, contractors, and data teams; and productionize auditable, low-latency inference services with confidence scoring, drift monitoring, and safe fallbacks. Work under medical-device design controls and support robust modeling across diverse patient anatomy and imaging conditions.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

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 manage a machine learning engineering team focused on making engineering drawings and CAD data usable for automation. Lead hiring, onboarding, mentorship, performance, technical direction, design reviews, and production deployment ownership. Guide annotation tooling, active learning, synthetic data augmentation, model health, and organizational growth while remaining technically hands-on and partnering across engineering, technical leadership, and business teams.

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.

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.

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.

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

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.

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.