Benefits:

• Equity options

• 5% 401(k) match

• Flexible working

• Enhanced parental leave

• Private healthcare

Education Requirements:

• Masters or PhD

Experience Requirements:

• At least 1 year industry experience in a commercial, non-research environment

• Foundations in data driven modelling and deep learning

• Hands-on experience in probabilistic methods and predictive modelling

• Expertise in Python (NumPy, SciPy, Pandas, TensorFlow, PyTorch)

• Deploying scalable, production-ready models

Other Requirements:

• Ability to travel to customer sites (2-3 weeks per quarter)

• Right to work status required

Responsibilities:

• Pre-processing and analyzing data for predictive modelling

• Developing innovative deep learning models

• Designing, building and testing data pipelines

• Integrating data science models with simulations

• Engaging in communication and presentation with technical teams and customers

Benefits:

• Interesting and challenging work

• Competitive salary and equity

• Learning and growth opportunities

• Visa sponsorship and relocation assistance

• Health, dental, and vision insurance

Experience Requirements:

• Broad view of the generative media space

• Awareness of new methods in the space

• Work published in ICCV, ICML, Neurips, or CVPR

Other Requirements:

• Proficiency in Python, torch, diffusers, and the fal Python SDK

Responsibilities:

• Develop new methods to solve customers problems

• Conduct novel training or architecture developments

• Fine-tune pre-existing models with novel datasets

• Iterate on and deploy new AI breakthroughs

Benefits:

• Interesting and challenging work

• Learning and growth opportunities

• Visa sponsorship and relocation assistance

• Health, dental, and vision insurance

• Regular team events and offsites

Experience Requirements:

• 5+ years of experience in data science or analytics

• Advanced-level SQL

• Proficiency in Python for modeling and experimentation

• Proficiency with dbt and orchestration tools

• Experience establishing data quality and governance

Other Requirements:

• Experience with API products or developer tools

• Exposure to cloud usage or compute efficiency data

• Interest in data systems for AI-driven workflows

Responsibilities:

• Architect metrics defining user success

• Develop causal understanding of customer discovery

• Own instrumentation standards and data contracts

• Surface insights through deep-dives

• Develop scalable data products

Benefits:

• Reduced teaching load (four weekly hours per semester)

• Excellent scientific environment

• Opportunities for collaboration with international partners

• Part of the Cluster of Excellence CASA

• Civil servant status potential (for W2/W3)

Education Requirements:

• Doctorate of outstanding quality

• Habilitation or equivalent academic achievement

Experience Requirements:

• Positive evaluation as a junior professor

• Top international publications

• Proof of suitability for academic teaching

• Strong social and leadership skills

• Experience in academic self-administration

Other Requirements:

• Willingness to participate in academic self-administration

• Interest in interdisciplinary research connecting computer science and society

• Ability to contribute to English-taught courses

Responsibilities:

• Conduct empirical research on IT Security from a psychology/social science perspective

• Address interaction of human users and technical systems

• Contribute to English-taught computer science or IT security programs

• Contribute to interdisciplinary collaborative research projects

• Participate in academic self-administration

Benefits:

• Flexible, remote environment

• Unique culture that thrives on transparency, communication, and creativity

• Healthy work/life balance

• Trust and flexibility to attend to outside commitments

Experience Requirements:

• Experience blending pharmacology, statistics, and AI

Responsibilities:

• Lead scientifically challenging projects

• Own projects end-to-end and collaborate with global experts

• Drive machine learning core

• Develop general methodology to embed ML into modeling structures

• Pharmacological applications research

Benefits:

• competitive salary

• three weeks of paid vacation per year

• phenomenal co-workers

Experience Requirements:

• at least 10 years of experience in machine learning development

• analysis of large datasets is required

Other Requirements:

• expertise in making inferences

• building a robust machine learning algorithm in AWS

Responsibilities:

• analyzing large amounts of clinical and field generated data

Benefits:

• Competitive salary

• 25 days paid annual vacation

• Flexible working hours

• Health Insurance

• Subsidized Multisport card

Education Requirements:

• Degree in Computer Science, Statistics, Applied Mathematics, or related field

Experience Requirements:

• At least 5 years of experience in software engineering and data science fields

• Strong knowledge of software engineering of scalable production systems

• Excellence with programming languages

• Strong knowledge of design patterns, OOP, multithreading, and databases

Other Requirements:

• Good experience in building processes and automated deployments

• Excellent problem-solving and analytical skills

• Strong mentorship skills

• Broad knowledge of current technological stack (Linux, PostgreSQL, Java, Python, R, Docker)

Responsibilities:

• Design and implement framework for automated data science models

• Collaborate with product and engineering teams

• Conduct research to stay up-to-date with DS/ML techniques

• Develop proof-of-concept and prototypes

• Design and implement experiments to validate models

Benefits:

• Training and knowledge-sharing sessions

• Conference attendance and networking

• Opportunity to give talks and submit papers

• Annual in-person team meetings with families

• Extreme company transparency

Education Requirements:

• BS, MS, PhD in quantitative field, such as Physics, Mathematics, Statistics, Engineering, or equivalent practical experience.

Experience Requirements:

• Experience with some form of Deep Learning (e.g. Image recognition, or NLP)

• Experience with programming in Python

• Experience with Reinforcement Learning (bonus)

• Work experience in Wind Energy or Smart Manufacturing fields (bonus)

Other Requirements:

• Good knowledge of statistics, data analysis, and modelling methods

• Problem solving skills for formulating problems from new datasets

• Good written and verbal communication

• Ability to work with minimal to no supervision

• Ability to work remotely with cross-cultural teams

Responsibilities:

• Support deployment of products for customers

• Internal product strengthening

• Initial data exploration and modelling

• Reinforcement Learning training

• Collaborate with backend, product, and AI teams

Experience Requirements:

• 1-3 years in analytics, preferably at a high-growth startup or tech company

Other Requirements:

• Advanced SQL skills (joins, CTEs, window functions)

• Excel/Google Sheets power user with Python/R capabilities

• Experience with BI tools (Metabase, Tableau, Looker, etc.)

• Experience with ETL pipelines or data engineering fundamentals

Responsibilities:

• Build on data infrastructure, clean data from 10+ sources, and design automation patterns

• Own end-to-end analytics for product, finance, growth, and operations

• Design self-serve analytics tools and documentation

• Build systems that turn manual reporting into automated intelligence

• Leverage AI tools and chatbots to accelerate analysis workflows

Education Requirements:

• MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, (or equivalent practical experience)

Experience Requirements:

• 3+ years of experience in applied data science / ML in a product environment (or equivalent practical experience)

Other Requirements:

• Strong Python skills and experience with common DS libraries (pandas, NumPy, scikit-learn)

• Solid SQL skills (joins, aggregations, window functions)

• Experience building predictive or anomaly detection models and performing rigorous evaluation

• Ability to translate business questions into measurable metrics and a clear analytical plan

• Experience working with messy real-world data: data validation, debugging pipelines, and collaborating on labeling/ground truth

Responsibilities:

• Deliver data science solutions end-to-end within a product squad

• Build, train, and improve ML models for supply chain use cases

• Define success metrics and evaluation plans with support from senior DS/PM

• Work with stakeholders to create and maintain ground truth

• Implement hybrid decision logic by combining ML outputs with statistical methods and SQL/rules-based logic

Experience Requirements:

• Fluent in Python and frameworks like PyTorch, JAX, or TensorFlow

• Experience in ML research or production-grade ML systems

• Track record of publication in tier-1 venues (NeurIPS, ICML, etc.)

Other Requirements:

• Ability to move fast from paper to prototype

• Focus on efficiency and scalability

• Preference for small, deep-technical teams

Responsibilities:

• Design and implement novel architectures and training methods

• Translate scientific ideas into working systems

• Publish original research

• Deploy adaptive intelligence systems

• Collaborate with core foundation model and systems teams

Experience Requirements:

• Understanding of the Japanese model evaluation landscape

• Familiarity with Japanese pre-training data sources

• Experience with Huggingface inference, vLLM, and cloud APIs

Other Requirements:

• Native Japanese speaker

• Motivation to adapt models to new cultures and workflows

• Ability to catch and fix LLM edge cases

Responsibilities:

• Identify and curate high-quality Japanese text and audio datasets

• Design methods to synthetically generate Japanese training data

• Train and fine-tune models for Japanese enterprise use cases

• Adapt existing LFMs for Japanese culture

• Implement evaluation frameworks for Japanese datasets

Benefits:

• Flexible vacation (annual/half/half-half)

• Refresh leave (4 days)

• Birthday half-day off

• Conference and IT seminar participation

• Health check-up support

Education Requirements:

• Master's or Ph.D. in AI-related fields

• Major in Mechanical, Computer, Electronic, or Industrial Engineering

Experience Requirements:

• SOTA AI research in engineering or manufacturing

• Knowledge in CAD, CAE, CAM, or optimal design

• Experience with 3D data and LLM research

Other Requirements:

• Ability to quickly learn and spread new technologies

• Excellent teamwork and communication skills

• Eligibility for military service exemption

Responsibilities:

• Research generative/predictive AI for 3D/2D/1D data

• Develop Agentic AI for autonomous design

• Research CAE analysis automation agents

• Implement Multi-Agent System based design automation

• Advancing AI solutions through cutting-edge research

Experience Requirements:

• 3 - 7 years

Education Requirements:

• Graduate or postgraduate degree in Computer Science, Statistics, Analytics, or Data Science

Experience Requirements:

• Role available at multiple levels (Jr, Sr, Principal)

• Experience deploying NLP solutions in a commercial environment

• Strong experience implementing models in production

Other Requirements:

• Deep understanding of machine learning and deep learning algorithms

• Expertise in developing NLP/NLU algorithms and models

• Programming skills in Python and R

• Knowledge of tools like TensorFlow, Keras, MXNET, and H2O

• Experience with chatbot technologies like Elasticsearch and Solr

Responsibilities:

• Research and develop algorithms for learning from text

• Extract data sets containing millions of documents

• Develop NLP capabilities to improve client service speed

• Summarize research and analysis for stakeholders

• Apply advancements in AI and deep tech to product needs

Education Requirements:

• Graduate degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science

Experience Requirements:

• 7+ years of experience as a Data Scientist or Machine Learning Solutions Architect

• 5+ years of proficiency in Python for data analysis, model training, evaluation, deployment, and optimization

• 1+ year of experience with technologies related to large language models

Other Requirements:

• Experience with open source frameworks like LangChain and LlamaIndex

• Knowledge of prompt engineering and state-of-the art model architectures

• Familiarity with AWS, Azure & Google services and the cloud computing landscape

• Knowledge of model deployment technologies such as TorchServe, ONNX, Triton, vLLM

• Familiarity with big data technologies such as Hadoop, Spark, and MongoDB

Responsibilities:

• Help lead the data science team fostering innovation and excellence

• Develop technical assets and IP across automated pentesting and real-time monitoring

• Engage with product owners to influence product direction

• Track and analyze emerging threats to AI systems

• Develop and implement detection and mitigation strategies for identified threats

Education Requirements:

• MS/PhD in Computer Science, Electrical Engineering, or a related field.

Experience Requirements:

• 2+ years of experience in computer vision, machine learning, and deep learning development.

• Proficiency in Python and C++ with hands-on programming skills; familiarity with embedded systems is a plus.

• Experience with Deep network development (visual data focus), object detection, tracking, and 3D computer vision.

• Experience with Structure from motion, network-based sensor fusion, and mathematical optimization.

• Familiarity with ADAS and autonomous driving technology, particularly in 3D object detection and semantic segmentation.

Other Requirements:

• Mandarin proficiency is a plus.

Responsibilities:

• Develop deep learning-based perception algorithms, including object detection, lane detection, semantic segmentation, depth estimation, curb detection, etc.

• Design and evaluate cutting-edge network structures and training methods for vision tasks.

• Implement network compression and quantization-aware training to optimize models for ASIC hardware deployment.

• Conduct prototype development, regression testing, benchmark testing, and performance evaluation.

• Prepare demos to showcase model performance and deploy solutions on embedded platforms.

Benefits:

• equity

• benefits

Education Requirements:

• Ph.D. in Computational Biology, Bioinformatics, Statistics, Biophysics, or related field, or equivalent experience

Experience Requirements:

• Expertise in RNA biology and biochemistry, RNA-protein interactions, and RNA structure

• Proficiency in Python for data curation and analysis at scale

• Strong programming background, familiarity with Unix

• Strong foundation in statistics and experience with conducting statistical analysis of large-scale datasets

Other Requirements:

• Authorized to work lawfully in the US

• Open to working in-person at South San Francisco several days a week

Responsibilities:

• Provide RNA biology and RNA structure expertise on the ML team

• Enable and apply RNA-structure platform to prioritize RNA targets

• Generate insights from datasets on RNA structures and small molecule interactions

• Curate RNA datasets for training of ML models

• Inform scientific questions and ML model development

Benefits:

• Equity

• Benefits

• Inclusive culture

• Safe environment

• Barrier-free workplace

Education Requirements:

• PhD in Physics, Electrical/Mechanical Engineering, or a closely related field

Experience Requirements:

• At least 2 years of postdoctoral or industry experience

• Proven track record designing, improving and characterizing SNSPDs

• Experience with high-bandwidth RF readout electronics

• Extensive hands-on experience operating cryostats

Other Requirements:

• Self-motivated and detail-oriented

• Excellent interpersonal and written communication skills

• Python programming experience preferred

Responsibilities:

• Develop record breaking single photon detectors

• Design, assemble, and evaluate SNSPDs from concept through validation

• Independently operate cryogenic systems (dilution refrigerators, etc.)

• Collaborate with internal and external process and packaging engineers

• Develop novel high-bandwidth, low latency RF electronics readout systems

Education Requirements:

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or Statistics

Experience Requirements:

• 7+ years of hands-on experience in applied machine learning and data science

• 2+ years in a leadership or managerial role

• Success in adapting foundation models through fine-tuning or transfer learning

Other Requirements:

• Expertise with PEFT approaches (LoRA, prefix tuning, etc.)

• Proficiency in PyTorch, TensorFlow, and Hugging Face

• Knowledge of GPU/TPU optimization and scaling ML workloads

Responsibilities:

• Lead and mentor a team of applied scientists and ML engineers

• Translate cutting-edge research into practical, scalable business solutions

• Design, evaluate, and improve models using robust validation strategies

• Collaborate with product, engineering, and business stakeholders

• Articulate complex ML concepts to technical and non-technical audiences