Calico: Researching aging biology to develop longevity-improving therapies.
5+ YOEPhD in computational biology, bioinformatics, computer science, or related field; strong publication record; 0-5 years (Scientist) or 5+ years (Senior Scientist) in industry or academia; deep ML expertise; genomics knowledge; onsite four days/week.
Python, TensorFlow, PyTorch, Genomics data, DNA sequence analysis
Tacit: Developing advanced hardware to rethink human-computer interaction.
PhD or equivalent experience in ML/computational neuroscience, expertise in deep learning, proficiency in PyTorch/TensorFlow and Python, experience deploying models, strong communication and collaboration skills.
FreenomeNASDAQ: FRNM: Develops blood tests for early cancer detection using machine learning.
6+ YOEPhD in quantitative field with 6+ years post-PhD industry/postdoc experience in applied ML/DL; demonstrated publications or impact; proficiency in Python/R/C/C++/Java; experience with deep learning, supervised/self-supervised/contrastive learning.
Hinge HealthNYSE: HNGE: Digital provider of musculoskeletal care and physical therapy
7+ YOEBachelor's in a quantitative field, 7+ years building and deploying ML systems at consumer scale, shipped recommendation/sequential-decision systems, strong experimentation and statistics, proficiency in Python and SQL.
Gilead SciencesNASDAQ: GILD: Develops and sells medicines for life-threatening infectious diseases.
2+ YOEPhD in a quantitative field with 2+ years' experience; strong Python and deep learning framework proficiency (PyTorch and/or JAX); experience training and evaluating representation, multimodal, geometric, or generative models; knowledge of protein structure and antibody biophysics.
RocheSIX Swiss Exchange: ROG: Develops and manufactures pharmaceutical medicines and diagnostic solutions.
PhD or equivalent in a quantitative field; deep ML expertise; hands-on quantum chemistry experience (Psi4, PySCF, ORCA, xTB); fluent in Python and PyTorch or JAX; publication record; experience building scalable ML pipelines and synthetic datasets.
Machine Learning Scientist - Apple Services Engineering, GenAI & ML Frameworks
San Francisco, California, United States
OnsiteFull Time
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Experienced ML scientist working on LLMs and GenAI, collaborating with product, infra, and foundation model teams to improve model reasoning, domain knowledge, tool use, and system integration.
7+ YOEPhD in a quantitative field, 7+ years post-PhD research experience building ML methods for biology; deep expertise in foundation models, sequence modeling, regulatory genomics, and proven scientific leadership and publication record.
Senior Machine Learning Scientist I, Drug Discovery Analytics
Redwood City, California, United States
$229k-$269k/yrHybridFull Time
Revolution MedicinesNASDAQ: RVMD: Developing precision oncology therapies for RAS-addicted cancers
6+ YOEPhD in a quantitative field; 6+ years applying ML to scientific datasets; expertise in Python and scientific libraries; experience with PyTorch/TensorFlow/scikit-learn, model development/validation, and noisy experimental data.
Gilead SciencesNASDAQ: GILD: Develops and sells medicines for life-threatening infectious diseases.
2+ YOEPhD in a quantitative discipline with 2+ years experience; proficiency in Python, deep learning (PyTorch/JAX), NumPy, pandas; experience architecting and evaluating deep learning models; knowledge of protein structure and antibody biophysics; demonstrated research productivity.
Sunday: Developing autonomous robots to perform household chores.
3+ YOE3+ years of ML work for robotics, Python and deep learning (PyTorch preferred), hands-on robot learning, data collection, and cross-functional collaboration.
CATHEXIS: Provides consulting and technology services to federal government agencies.
2+ YOEBachelor's in CS/EE/Statistics (MS/PhD preferred), ~2 years relevant experience, strong Python and applied ML skills, scalable ML experience, strong math and communication skills.
Python, MapReduce, Amazon AWS, Microsoft Azure, Google Cloud Services
Extropic: Developing thermodynamic computing hardware for energy-efficient AI.
Expertise in scientific Python and a deep learning framework, strong probability and linear algebra, publications in top ML venues, experience with training/deploying high-performance models and related infrastructure.
Neo.Tax: Automating enterprise accounting and R&D tax credit calculations.
6+ YOE6+ years in data science / ML shipping production models; strong Python, SQL; experience building data pipelines; production ML, experimentation, and cross-functional collaboration.
Scale AI: Provides data and infrastructure for training artificial intelligence models.
5+ YOE5+ years as an ML engineer or applied scientist with production ML/LLM systems; experience building evaluation/monitoring or continuous-learning infrastructure; strong experimentation and collaboration skills.
Plaid: Provides financial data connectivity and payment infrastructure via APIs.
7+ YOESenior ML engineer with 7–12+ years (MS) or 5–9+ years (PhD); strong technical leadership; expertise in transformers/LLMs; end-to-end production ownership; Python and software engineering fundamentals; fintech domain experience a plus.
Python, PyTorch, TensorFlow, Distributed training, Pretraining infrastructure, ML platforms
Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence
Palo Alto or New York or Seattle
$164k-$260k/yrOnsiteFull Time
JPMorgan ChaseNYSE: JPM: Global financial services firm providing banking and investment solutions.
3+ YOEPhD with 3+ years or MS with 5+ years in ML/GenAI; strong GenAI, ML/DL, Python tooling; experimental design and production deployment experience.
Senior research Scientist - Machine Learning Systems & Efficiency Engineer
Seattle or San Francisco or San Jose
$143k-$271k/yrOnsiteFull Time
AdobeNASDAQ: ADBE: Provides software for digital media creation and marketing analytics
Master's or PhD in CS/EE or related; deep expertise in ML systems, distributed inference, GPU performance, and production deployment; proficiency in Python and C++; experience with Triton/CUDA and performance profiling.