Machine Learning Research Engineer, GenAI Applied ML Job at Scale (San Francisco)

Principal Machine Learning Engineer

This is a high-leverage leadership role that spans architecture, execution, and ...

Location

India , Bengaluru

Salary:

Not provided

Ema

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s (or PhD) degree in Computer Science, Machine Learning, Statistics, or a related field
A strong track record (usually 10-12+ years) of applied experience with ML techniques, especially in large-scale settings
Experience building production ML systems that operate at scale (latency / throughput / cost constraints)
Experience in Knowledge retrieval and Search space
Exposure in building Agentic Systems and Frameworks
Proficiency in relevant programming languages (e.g. Python, C++, Java) and ML frameworks (TensorFlow, PyTorch, etc.)
Strong understanding of the full ML lifecycle: data pipelines, feature engineering, model training, serving, monitoring, maintenance
Experience designing systems for monitoring, diagnostics, logging, model versioning, etc.
Deep knowledge of computational trade-offs: distributed training, inference, optimizations (e.g. quantization, pruning, batching)
Excellent communication skills

Job Responsibility

Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products
Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning
Define and own the multi-year ML roadmap for GenAI infrastructure — including agent frameworks, RAG systems, world-class evaluation loops, and integration with MCP, browser, and vision pipelines
Identify and integrate cutting-edge ML methods / research (deep learning, large models, recommender systems, LLMs, etc.) into Ema’s products or infrastructure
Research, prototype, and integrate cutting-edge ML and LLM advancements (reasoning, memory architectures, multi-modal perception, long-context models, autonomous agents) into the platform
Optimize trade-offs between accuracy, latency, cost, interpretability, and real-world reliability across the agent lifecycle — from prompt design to orchestration and execution
Champion engineering excellence — drive observability, reproducibility, versioning, testing, and bias-aware development across ML and agentic systems
Mentor and elevate senior engineers and researchers, fostering a culture of scientific rigor, experimentation, and system-level thinking
Collaborate cross-functionally with product, infra, and research teams to align ML innovation with enterprise needs — enabling secure integrations, privacy-aware deployments, and scalable use cases
Influence data strategy — guide how retrieval indices, embeddings, structured/unstructured corpora, and feedback loops evolve to improve grounding, factuality, and reasoning depth

Fulltime

Engineer 2, Machine Learning

Responsible for contributing to the development and deployment of machine learni...

Location

India , Chennai

Salary:

Not provided

Comcast Advertising

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field
3–4 years of hands-on experience in ML engineering, ML testing, or applied ML roles
Strong understanding of ML fundamentals, debugging, and evaluation methodologies
Strong proficiency in Python
Hands-on experience with ML frameworks (scikit-learn, PyTorch, TensorFlow)
Experience building or extending testing frameworks (pytest, unittest)
Solid skills in Pandas, NumPy, and data analysis
Experience or exposure to LLMs and GenAI concepts: Prompt engineering, LLM evaluation techniques, RAG pipelines (basic understanding)
Familiarity with ML pipelines, model deployment workflows, and CI/CD
Curious mindset with interest in GenAI and LLM-driven automation

Job Responsibility

Contributes to the implementation, refinement and validation of machine learning algorithms for products and applications
Trains machine learning models, validates the accuracy of the machine learning models once trained and deploys validated machine learning models into production
Contributes to designs and development of data pipelines consisting of data ingest, data validation, data cleaning and data monitoring
Researches, writes and edits documentation and technical requirements, including evaluation plans, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports
Contributes to the company by creating patents, Application Programming Interfaces (APIs) and other intellectual property
Contributes to the testing and evaluation of solutions presented to the Company by various internal and external partners and vendors
Contributes to case studies, testing and reporting
Designs proof of concept solutions and contributes to studies to support future product or application development
Consistent exercise of independent judgment and discretion in matters of significance
Regular, consistent and punctual attendance

What we offer

Paid Time off
Physical Wellbeing benefits
Financial Wellbeing benefits
Emotional Wellbeing benefits
Life Events + Family Support benefits

Fulltime

Sr. Scientist, UberEats Applied AI (Machine Learning)

Working at Uber means solving hard problems in a high-stakes, fast-moving enviro...

Location

United States , San Francisco; Sunnyvale

Salary:

190000.00 - 211000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields
Minimum 4 years of industry experience as an Applied or Data Scientist or equivalent (2+ years if holding a Ph.D.)
Proficiency in Python or R with experience handling large-scale datasets using Spark, Hive, or PySpark
Proven experience in building and training Deep Learning models
Solid understanding of statistical methods, experimental design, and A/B testing

Job Responsibility

Design and implement ML algorithms and objective functions that unify competing business interests like organic relevance and sponsored content into a single value space
Act as the science lead for foundational machine learning initiatives, unblocking technical debt and optimizing feature engineering for high-scale, real-time systems
Navigate the ambiguity of user behavior by designing sophisticated experiments and causal inference frameworks that go beyond standard A/B testing
Collaborate across disciplines (Product, Engineering, and Data Science) to translate high-level business goals into theoretically sound and performant technical roadmaps
Research and apply advancements in Deep Learning, Reinforcement Learning, and GenAI to solve complex, high-impact problems without a clear starting point
Own your algorithms/ML workflow, from the first scientific hypothesis to debugging production issues in real-time, low-latency environments

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits (details at provided link)

Fulltime

Staff Applied AI Engineer, Enterprise GenAI

The SGP ML team works on the front lines of this AI revolution. We interface dir...

Location

United States , San Francisco, CA; Seattle, WA; New York, NY

Salary:

216000.00 - 270000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

7+ years of full-time engineering experience, post-graduation
A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client's business goals
Strong engineering background: a Bachelor's degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background
Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Job Responsibility

Own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems
Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
Have experience gathering business requirements and translating them into technical solutions
Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases
Be able and willing to multi-task and learn new technologies quickly

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
commuter stipend

Fulltime

Applied AI Engineer, Enterprise GenAI

The SGP ML team works on the front lines of this AI revolution. We interface dir...

Location

United States , San Francisco; New York

Salary:

180600.00 - 225750.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background
Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Job Responsibility

Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
Have experience gathering business requirements and translating them into technical solutions
Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases
Be able and willing to multi-task and learn new technologies quickly

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO

Fulltime

Machine Learning Tech Lead, GenAI

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...

Location

Salary:

Not provided

Provectus

Expiration Date

Until further notice

Requirements

Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
Strong expertise in AWS Cloud Services
Strong experience in ML/AI, including at least 2 years in a leadership role
Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
Familiarity with MLOps tools and best practices
Excellent problem-solving and decision-making abilities
Strong communication skills and the ability to lead cross-functional teams
Passion for mentoring and developing engineers

Job Responsibility

Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment
Drive the roadmap for machine learning projects aligned with business goals
Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery
Design, develop, and fine-tune LLMs and other machine learning models to solve business problems
Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction
Stay ahead of advancements in LLMs and apply emerging technologies
Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML
Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.)
Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS
Ensure best practices in security, monitoring, and compliance within the cloud infrastructure

What we offer

Long-term B2B collaboration
Fully remote setup
Comprehensive private medical insurance or budget for your medical needs
Paid sick leave, vacation, public holidays
Continuous learning support, including unlimited AWS certification sponsorship

Staff Applied Research Scientist - Martech AI

We are seeking a highly experienced and strategic Staff Applied Research Scienti...

Location

United States , New York City; Palo Alto; Chevy Chase; Dallas; Seattle; Chicago; Austin

Salary:

130000.00 - 260000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

BS in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, PhD is preferred
At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact
Demonstrated ability to leverage LLMs and agentic AI systems to develop and deploy personalized marketing solutions, including individualized content generation, campaign targeting, and optimization of customer engagement/retention/conversion strategies
Strong proficiency in Python and SQL
deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization
Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams
Strong written and verbal communication skills
ability to set the right context and explain complex technical topics to varied audiences, including executives

Job Responsibility

Identify High-Impact Opportunities: Proactively surface and shape high-value AI/ML initiatives by engaging with product, engineering, and operations to align technical roadmaps with strategic business goals
Architecture & Technical Direction: Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems
Development & Productionization: Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery
ROI Measurement & Experimentation: Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments
Innovation & Research Integration: Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem
Set technical direction for multi-quarter research initiatives
build evaluation frameworks, ensure reproducibility/responsible AI, and drive cross-functional adoption
shepherd patents
Cross-Functional Collaboration: Champion collaboration across Product, Engineering, Data Platform, Governance, Legal, and Operations to ensure responsible, compliant, and effective adoption of AI systems
Mentorship & Capability Building: Mentor junior and senior scientists, elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

Applied Scientist II, GenAI Evaluation Media (GEM)

The North America Stores GenAI Evaluation Media (GEM) team is seeking an Applied...

Location

United States , Sunnyvale; Seattle

Salary:

142800.00 - 222200.00 USD / Year

Amazon

Expiration Date

Until further notice

Requirements

PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience in building models for business application
Experience programming in Java, C++, Python or related language

Job Responsibility

Develop core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI
Design and implement visual agentic systems, balancing visual quality, relevance, latency, and cost
Define metrics and success criteria for scientific initiatives, ensuring rigorous validation across customer touch points
Own end-to-end delivery of research initiatives from problem formulation through experimentation to production deployment
Stay current with latest advances in AI/ML and identify opportunities to apply them to problem space
Drive development and deployment of scalable agentic systems for visual content understanding and generation
Maintain high scientific and engineering standards in work
Tackle complex technical problems while maintaining practical focus on customer value
Contribute to team's culture of scientific excellence through presentations and publications at internal and external science forums
Partner with product and engineering teams to deliver customer-facing features

What we offer

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

Fulltime

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Machine Learning Research Engineer, GenAI Applied ML

Job Description

Job Responsibility

Requirements

Nice to have

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