Member of Technical Staff, Machine Learning Datasets Job at Runway

Staff Machine Learning Engineer

We are seeking a Staff Machine Learning Engineer to join our Foundation AI team....

Location

United States , Boston

Salary:

170000.00 - 230000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, Electrical Engineering, or a related field, or equivalent professional experience
7+ years of experience in applied ML, AI research, or large-scale modeling, with a track record of delivering production systems
Expertise in modern deep learning (e.g., transformers, state space models) and multimodal model training
Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
Experience building and scaling large datasets and training large models in distributed compute environments
Strong applied experience with representation learning, self-supervised methods, and fine-tuning for downstream applications
Familiarity with MLOps best practices including model versioning, evaluation, CI/CD for ML, and cloud-based compute
Excellent communication skills and ability to collaborate cross-functionally with engineers, researchers, and product teams
Passion for WHOOP’s mission to improve human performance and extend healthspan through science and technology

Job Responsibility

Design, train, and optimize large-scale multimodal foundation models that integrate wearable sensor data, text, biomarkers, and behavioral data
Conduct applied research in self-supervised learning, representation learning, and downstream task fine tuning to advance WHOOP’s core model capabilities
Develop scalable, distributed training pipelines for large models on high-performance compute environments
Collaborate with MLOps, data engineering, and software engineering teams to operationalize models for production deployment, ensuring robustness, reproducibility, and observability
Partner with product and research teams to translate foundation model capabilities into downstream features that deliver meaningful member value
Contribute to the technical roadmap and architectural direction for foundation model development at WHOOP
Serve as a technical mentor for other data scientists, sharing best practices in deep learning, large-scale training, and multimodal data integration
Ensure models adhere to WHOOP’s standards for ethical, transparent, and privacy-preserving AI

What we offer

competitive base salaries
meaningful equity
benefits
generous equity package

Fulltime

Member of Technical Staff, AI Training Infrastructure

As a Training Infrastructure Engineer, you'll design, build, and optimize the in...

Location

United States , San Mateo

Salary:

175000.00 - 220000.00 USD / Year

Fireworks AI

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience
3+ years of experience with distributed systems and ML infrastructure
Experience with PyTorch
Proficiency in cloud platforms (AWS, GCP, Azure)
Experience with containerization, orchestration (Kubernetes, Docker)
Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)

Job Responsibility

Design and implement scalable infrastructure for large-scale model training workloads
Develop and maintain distributed training pipelines for LLMs and multimodal models
Optimize training performance across multiple GPUs, nodes, and data centers
Implement monitoring, logging, and debugging tools for training operations
Architect and maintain data storage solutions for large-scale training datasets
Automate infrastructure provisioning, scaling, and orchestration for model training
Collaborate with researchers to implement and optimize training methodologies
Analyze and improve efficiency, scalability, and cost-effectiveness of training systems
Troubleshoot complex performance issues in distributed training environments

What we offer

meaningful equity in a fast-growing startup
comprehensive benefits package

Fulltime

New

Data Scientist

The Data Scientist plays a pivotal role in planning, executing, and delivering m...

Location

United States , Camden

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Master’s, or PhD in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field
Specialization in ML, AI, cognitive science, or data science is highly preferred
3-5 years of hands-on experience planning and executing end-to-end data science projects with demonstrated impact on clinical or operational outcomes in business environments
Advanced programming proficiency in Python or R with strong expertise in machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and statistical analysis tools
Expertise in machine learning and statistical techniques including supervised/unsupervised learning, deep learning, NLP, computer vision, regression models, ensemble methods, and experimental design (A/B testing)
Strong data engineering capabilities including SQL/NoSQL database programming, distributed computing tools (Hadoop, Spark, Kafka), data pipeline development, and experience with cloud platforms (AWS, Azure, GCP)
Production ML and MLOps experience including model deployment, monitoring, containerization (Docker, Kubernetes), version control, and applying DevOps principles to data science workflows
Data visualization and communication excellence with ability to create compelling dashboards (Tableau, Power BI), translate complex technical findings into actionable insights, and present to diverse audiences from executives to frontline staff
Cross-functional collaboration skills with proven ability to work in agile environments, partner with stakeholders to align technical solutions with business objectives, and mentor junior team members
Healthcare domain knowledge preferred, particularly experience with Epic EHR systems, clinical workflows, and healthcare data standards, along with relevant certifications (Clarity /Caboodle, Google Cloud ML Engineer, AWS ML Specialist)

Job Responsibility

Collect, clean, and analyze datasets from diverse internal and external sources, applying advanced data wrangling techniques
Acquire access to various databases and source systems (SQL, NoSQL, graph databases) and create data pipelines
Apply statistical analysis and visualization techniques to explore and prepare data
Design, develop, and validate machine learning, statistical, and optimization models
Select appropriate algorithms and models for AI/ML and test them for accuracy, robustness, and fairness
Perform feature selection and engineering
Integrate domain knowledge into ML solutions
Conduct controlled experiments (A/B and multivariate testing)
Collaborate with MLOps, data engineers, and IT to evaluate deployment options
Continuously monitor execution and health of production ML models

Fulltime

Member of Technical Staff - ML Research Engineer, Data

Our Data team powers Liquid Foundation Models across pre-training, vision, audio...

Location

United States , San Francisco; Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Strong Python skills with the ability to quickly comprehend problems and translate them into clean, working code
Solid ML fundamentals: experience training, evaluating, and iterating on models (PyTorch preferred)
Track record of learning new technical domains quickly
3+ years relevant experience with an M.S., or 1+ year with a Ph.D. (5+ years with a B.S.)

Job Responsibility

Build and maintain data processing, filtering, and selection pipelines at scale
Create pipelines for pretraining, midtraining, SFT, and preference optimization datasets
Design synthetic data generation systems using LLMs, structured prompting, and domain-specific generators
Design and run evaluations and ablations to measure dataset's impact on model performance
Monitor public datasets across text, vision, and audio domains
Collaborate with pre-training, vision, and audio teams on modality-specific data needs

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

Member of Technical Staff, MLE

This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of ...

Location

Singapore

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Strong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions
Fluency with Python and core ML/LLM frameworks
Experience working with (or the ability to learn) large-scale datasets and distributed training or inference pipelines
Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies
Demonstrated ability to meaningfully shape LLM performance
A broad view of the ML research landscape and a desire to push the state of the art
Bias toward action, high ownership, and comfort with ambiguity
Humility and strong collaboration instincts
A deep conviction that AI should meaningfully empower people and organizations

Job Responsibility

Contribute to the design and delivery of custom LLM solutions for enterprise customers
Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies
Build custom models using Cohere’s foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets
Develop SOTA modeling techniques that directly enhance model performance for customer use-cases
Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks
Work as part of Cohere’s customer facing MLE team to identify high-value opportunities where LLMs can unlock transformative impact to our enterprise customers

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Member of Technical Staff, MLE

Our mission is to scale intelligence to serve humanity. We’re training and deplo...

Location

United States; Canada , San Francisco; New York; Toronto; Montreal

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Strong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions
Fluency with Python and core ML/LLM frameworks
Experience working with (or the ability to learn) large-scale datasets and distributed training or inference pipelines
Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies
Demonstrated ability to meaningfully shape LLM performance
A broad view of the ML research landscape and a desire to push the state of the art
Bias toward action, high ownership, and comfort with ambiguity
Humility and strong collaboration instincts
A deep conviction that AI should meaningfully empower people and organizations

Job Responsibility

Contribute to the design and delivery of custom LLM solutions for enterprise customers
Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies
Build custom models using Cohere’s foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets
Develop SOTA modeling techniques that directly enhance model performance for customer use-cases
Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks
Work as part of Cohere’s customer facing MLE team to identify high-value opportunities where LLMs can unlock transformative impact to our enterprise customers

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Member of Technical Staff, Pre-Training Data

As a Machine Learning Engineer specializing in pretraining data, you will play a...

Location

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Strong software engineering skills, with proficiency in Python and experience building data pipelines
Familiarity with curriculum learning, data mixing and data attribution
Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools
Experience working with large-scale datasets, including web data, code data, and multilingual corpora
Knowledge of data quality assessment techniques and experimentation with data mixtures
A passion for bridging research and engineering to solve complex data-related challenges in AI model training

Job Responsibility

Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance
Develop robust data modeling techniques to ensure datasets are structured and formatted for optimal training efficiency
Research and implement innovative data curation methods, leveraging Cohere’s infrastructure to drive advancements in natural language processing
Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime