AI Jobs

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

Education Requirements:

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

Experience Requirements:

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

• Experience training and fine-tuning large-scale models (LLMs, transformers)

• Experience working on applied AI problems across NLP or computer vision

Other Requirements:

• Hands-on expertise with PEFT approaches such as LoRA

• Proficiency in PyTorch, TensorFlow, and Hugging Face

• Knowledge of GPU/TPU optimization and mixed precision training

Responsibilities:

• Design, evaluate, and improve models using validation strategies

• Adapt foundation models to domain-specific applications

• Collaborate with product and engineering stakeholders

• Translate research into practical, scalable solutions

• Provide technical guidance to junior scientists

Education Requirements:

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

Experience Requirements:

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

• Experience in training and fine-tuning large-scale models

• Proven record of adapting foundation models through transfer learning

Other Requirements:

• Expertise in PEFT approaches and quantization-aware training

• Proficiency in Spark, Databricks, or cloud-native ML services

• Excellent communication and presentation skills

Responsibilities:

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

• Design, evaluate, and improve models using bias/fairness checks

• Work with product and engineering teams to deliver AI solutions

• Translate research breakthroughs into scalable production systems

• Ensure performance optimization of AI models

Education Requirements:

• PhD degree in computer science, engineering, a related field, or equivalent experience

Experience Requirements:

• 5+ years of experience in relevant jobs

• Proven track record of successful machine learning research projects

Other Requirements:

• First-author publications at peer-reviewed AI conferences

• Strong scientific understanding of generative AI

• Proficiency in frameworks like PyTorch or TensorFlow

Responsibilities:

• Deep understanding of machine learning research

• Manage and execute a research agenda

• Developing proof-of-concept models

• Preparation and writing of technical and scientific papers

Education Requirements:

• PhD degree in computer science, engineering, a related field, or equivalent experience

Experience Requirements:

• 5+ years of experience in relevant jobs

• Proven track record of successful machine learning research projects

Other Requirements:

• First-author publications at peer-reviewed AI conferences

• Strong scientific understanding of generative AI

• Proficiency in frameworks like PyTorch or TensorFlow

Responsibilities:

• Deep understanding of machine learning research

• Manage and execute a research agenda

• Developing proof-of-concept models

• Preparation and writing of technical and scientific papers

Benefits:

• Culture of mutual trust

• Professional growth opportunities

• Support and passion environment

Education Requirements:

• Currently pursuing a BSc, BEng or MSc in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related field

Experience Requirements:

• Strong knowledge of Python and libraries such as pandas, scikit-learn, PyTorch or TensorFlow

• Prior experience in AI/ML, Data Science, Banking/Financial Services, FinTech, or Consulting

• Fluent/native business-level English

Other Requirements:

• Available at least 10 hours per week

• Self-starter

• Strong analytical and problem-solving skills

Responsibilities:

• Developing and improving AI/ML models for detection of suspicious activities

• Researching and implementing state-of-the-art techniques in data science

• Improving process efficiency and automation across the Data Science team

• Building prototypes and proof-of-concepts for novel AI-driven approaches

• Analyzing complex financial datasets and identifying patterns

Education Requirements:

• Ph.D. in Computer Science, Electrical Engineering, or another relevant field

Experience Requirements:

• Prior experience in leadership roles within R&D teams, or as VP R&D/CTO

• In-depth expertise in Vision AI (perception)

• Strong coding skills, preferably in Python and CPP

• Experience in real-time, physical-world applications

Other Requirements:

• Adaptability

• Technical Insight

• Collaborative Mindset

• Self-Driven

• Detail-Oriented

Responsibilities:

• Address complex AI challenges as a versatile 'joker card'

• Expedite projects and solve technical bottlenecks

• Provide specialized expertise as needed to accelerate outcomes

• Foster a culture of growth and technical excellence

• Collaborate closely with internal teams and guide staff

Benefits:

• Equity option allocations

• Accreditation and tuition support

• Extended health and dental benefits

• Annual paid closure

• Parental leave top-up

Education Requirements:

• Graduate degree in geophysics, geology, or earth sciences

• Sub-specialization in data science is an asset

Experience Requirements:

• 8+ years experience analyzing and interpreting geophysical field data

• Advanced-level coding capabilities in Python

• Experience in technical sales support is an asset

• Understanding of geophysical methods and inversions

• Proficiency using geophysical analysis software

Other Requirements:

• Legally able and currently documented to work full-time hours in Canada

• Professional level communication skills in English

• P.Geo. certification or eligibility to register

• Detail-oriented and committed to high quality work

Responsibilities:

• Analyze, model, and interpret geophysical data

• Interact with prospective and current customers to understand problems

• Propose technically feasible solutions that create value

• Perform geophysical data quality assessment and processing

• Process and analyze data using Python and Geoscience ANALYST

Benefits:

• industry leading competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• Ph.D., M.D., or equivalent advanced degree in cancer biology, molecular biology, pharmacology, computational biology, or a related discipline

Experience Requirements:

• Typically 12–20+ years of relevant experience in biotech or pharma

• Success advancing at least one oncology program into clinical development

• Deep expertise in translational science (biomarkers, MoA, resistance, combination biology)

• Experience working with large, complex translational and/or clinical datasets

• Track record of leading cross-functional teams

Other Requirements:

• Strong working knowledge of AI/ML concepts as applied to drug discovery

• Excellent scientific storytelling and communication skills

Responsibilities:

• Lead Portfolio-Level Translational Strategy

• Define Biomarker & Patient Selection Strategy

• Direct Mechanism of Action, Resistance & Combination Biology

• AI/ML-Enabled Translational & Clinical Prediction

• Build and Lead a High-Impact Organization

Benefits:

• industry leading competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• PhD in biochemistry, cell biology, cancer biology, pharmacology, or related discipline

• MS with 7+ years of experience

• BS with 9+ years of experience

Experience Requirements:

• At least 2 - 8 years of relevant academic or industry experience for PhD holders

• Experience in cancer research, mechanism of action/resistance, or translational biomarker development

• Hands-on experience in in vivo pharmacology (PK/PD, efficacy studies)

• Oversight and coordination of in vivo studies at CROs

• Proficiency in cell and molecular biology (cell culture, ELISA, Western blotting, qPCR, flow cytometry)

Other Requirements:

• Excellent communication skills

• Ability to work collaboratively across teams

• Highly motivated to learn new technologies

Responsibilities:

• Design and develop translational studies for various programs

• Design and manage in vivo pharmacology studies at CROs

• Design and execute hands-on experiments in cell and molecular biology

• Analyze and interpret data from internal experiments and CRO deliverables

• Conduct literature reviews to support mechanism of action and biomarker strategies

Benefits:

• industry leading competitive pay

• company paid healthcare

• flexible spending accounts

• voluntary life insurance

• 401K matching

Education Requirements:

• BS in Chemistry with 5+ years experience (pharma/biotech)

• MS in Chemistry with 3+ years experience (pharma/biotech)

Experience Requirements:

• Proven skills in multi-step organic synthesis and reaction optimization

• Experience in SAR analysis and scientific presentation

• Prior exposure to high-throughput experimentation (preferred)

• Familiarity with ADME-PK principles (preferred)

• Experience with molecular modeling and structure-based drug design (preferred)

Other Requirements:

• Ability to thrive in a fast-paced, highly collaborative research environment

• Availability to work onsite in San Diego

Responsibilities:

• Design, synthesize, purify, and characterize chemical compounds (10 mg–5 g scale)

• Identify and optimize reaction conditions using screening kits

• Collaborate with the high-throughput experimentation team

• Analyze biological and ADME-PK data using cheminformatics tools

• Partner with computational chemists to leverage machine learning insights