Machine Learning Research Engineer, Agents - Enterprise GenAI Job at Scale (San Francisco)

New

Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI

Join the team shaping the future of AI at Scale. The Enterprise ML Research Lab ...

Location

United States , San Francisco; New York

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

3+ years of building with LLMs in a production environment
Clear experiences with constructing high quality data to use to improve an LLM/Agent
Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
PhD or Masters in Computer Science or a related field

Job Responsibility

Build synthetic data pipelines to generate enterprise environments to use for RL post-training
Create agents to convert traces from production into actionable insights to use to improve agents
Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms
Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers

What we offer

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

Fulltime

New

Staff Machine Learning Research Engineer, Agent Post-training - Enterprise GenAI

Build out our next-gen Agent RL training platform; build out the platform that w...

Location

United States , San Francisco; New York

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

5+ years of LLM training in a production environment
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
PhD or Masters in Computer Science or a related field

Job Responsibility

Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers
Research cutting edge algorithms to integrate directly into our training stack
Design solutions that enable complex multi-agent systems to directly learn from both process + outcome based rewards

What we offer

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

Fulltime

New

Senior/Staff Machine Learning Engineer, General Agents, Enterprise GenAI

Scale AI is the data foundation for AI, helping organizations build and deploy r...

Location

United States , San Francisco; New York

Salary:

218000.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases
Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience
Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design
Proven proficiency in Python, including writing production-quality, testable, and maintainable code
Experience building systems that integrate models with external tools, APIs, databases, and services
Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints
Strong communication skills and comfort working in customer-facing or cross-functional environments

Job Responsibility

Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases
Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints
Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings
Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs
Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems
Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage
Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level

What we offer

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

Fulltime

New

Machine Learning Systems Research Engineer, Agent Post-training - Enterprise GenAI

The Enterprise ML Research Lab works on the front lines of this AI revolution. W...

Location

United States , San Francisco; New York

Salary:

218400.00 - 273000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

At least 1-3 years of LLM training in a production environment
Passionate about system optimization
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster
Experience with multi-node LLM training and inference
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills to operate in a cross functional team environment
PhD or Masters in Computer Science or a related field

Job Responsibility

Build, profile and optimize our training and inference framework
Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements
Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation
Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
additional benefits such as a commuter stipend
equity based compensation

Fulltime

New

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

New

Director, Applied AI Engineering- Enterprise

Join the team shaping the future of AI at Scale. The Applied AI team works on th...

Location

United States , San Francisco; New York

Salary:

285200.00 - 356500.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

8+ years of experience building, deploying, and scaling ML systems in production, including Enterprise-grade Gen AI and agentic applications
6+ years of people leadership experience, including managing managers and leading multi-team organizations delivering customer-facing AI products
Deep applied expertise in Gen AI, including LLM-based systems, agent orchestration, evaluation and reliability frameworks, and production system design
Experience owning end-to-end AI product delivery—from problem definition and technical architecture to deployment, iteration, and scaling
Strong technical judgment across software engineering, system design, and applied ML fundamentals
Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners
Bachelor’s degree required
Master’s or PhD in Computer Science or a related field strongly preferred

Job Responsibility

Drive enterprise impact with GenAI: Partner directly with customers to identify high-leverage opportunities for generative AI, design solutions, and deliver production systems that create clear business value
Lead and scale a GenAI-native Applied AI organization: Build, mentor, and manage multiple teams of Applied AI Engineers and ML Engineers who are native to modern GenAI technologies, agentic systems, and multimodal models
Set technical and strategic direction: Define best practices for agent development, evaluation, deployment, and iteration across customer engagements and internal product efforts
Bridge frontier research to real-world applications: Translate advances in LLMs, multimodal models, and agentic workflows into practical, scalable solutions across industries
Discover model limitations and inspire innovation: Identify failure modes, inefficiencies, and gaps in current models
use these insights to influence internal research, product roadmaps, and customer strategy
Partner cross-functionally: Work closely with Product, Research, Sales, and Leadership to shape Applied AI offerings, prioritize investments, and guide long-term platform evolution
Influence the broader AI ecosystem: Represent Scale’s Applied AI capabilities with customers and partners, and help position Scale as a trusted leader in enterprise GenAI deployment

What we offer

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

Fulltime

Sr Machine Learning Engineer

We are seeking a Sr Machine Learning Engineer—Amgen’s most senior individual-con...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

3-5 years in AI/ML and enterprise software
Comprehensive command of machine-learning algorithms—regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques
Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale
Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, Semantic Kernel)
Proficiency in Python and Java
containerisation (Docker/K8s)
cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines)
Strong business-case skills—able to model TCO vs. NPV and present trade-offs to executives
Exceptional stakeholder management
can translate complex technical concepts into concise, outcome-oriented narratives

Job Responsibility

Engineer end-to-end ML pipelines—data ingestion, feature engineering, training, hyper-parameter optimisation, evaluation, registration and automated promotion—using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks
Harden research code into production-grade micro-services, packaging models in Docker/Kubernetes and exposing secure REST, gRPC or event-driven APIs for consumption by downstream applications
Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency
Optimise performance and cost at scale—selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantisation/pruning, and tuning GPU/CPU auto-scaling policies to meet strict SLA targets
Instrument comprehensive observability—real-time metrics, distributed tracing, drift & bias detection and user-behaviour analytics—enabling rapid diagnosis and continuous improvement of live models and applications
Embed security and responsible-AI controls (data encryption, access policies, lineage tracking, explainability and bias monitoring) in partnership with Security, Privacy and Compliance teams
Contribute reusable platform components—feature stores, model registries, experiment-tracking libraries—and evangelise best practices that raise engineering velocity across squads
Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness
Partner with data scientists to prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs

AI Engineer

About Blue Altair: Have you thought about the role you’ll play in the AI univers...

Location

India , Pune; Bangalore

Salary:

Not provided

Blue Altair

Expiration Date

Until further notice

Requirements

Master’s degree or relevant degree/certification in quantitative discipline, e.g., Computer Science, Mathematics, Statistics, Artificial Intelligence
Hands-on experience with statistical software tools. We prefer experience in Python and Python statistical libraries. Experience in R is also accepted, as is SAS, SPSS, Strata, and MATLAB
Deep conceptual understanding of probability & statistics, ML algorithm intuition, and computer science fundamentals
Deep experience in statistical and machine learning techniques such as classification, regression, feature selection and feature engineering, hyperparameter tuning, unsupervised learning methods, time series analysis, forecasting etc
Deep understanding of GenAI Models training and fine tuning of them
Proven experience in Generative AI (GenAI) including model training, fine-tuning, and deployment
Practical expertise with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Claude, etc
Experience implementing Retrieval-Augmented Generation (RAG) pipelines using Vector Databases (e.g., Pinecone, Weaviate, Milvus, FAISS)
Strong knowledge of Embeddings (text, image, multimodal) and their application in semantic search, personalization, and recommendation systems
Familiarity with Agentic AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) for building autonomous and multi-agent systems

Job Responsibility

Research, design, and implement GenAI-powered solutions for complex business problems
Build and deploy LLM-based applications including chatbots, copilots, and autonomous agents
Architect and optimize RAG pipelines for enterprise knowledge retrieval and augmentation
Develop and evaluate embedding-based solutions for semantic search, personalization, and recommendation
Experiment with agentic AI frameworks to design multi-agent workflows and autonomous decision-making systems
Research machine learning algorithms develop solution formulations, and test on large datasets
Given unstructured and complex business problems, design and develop tailored analytic solutions
Design experiments, test hypotheses, and build actionable models
Solve analytical problems and effectively communicate methodologies and results
Draw relevant inferences and insights from data including identification of trends and anomalies

What we offer

competitive compensation package
abundant opportunities for you to achieve, excel, and surpass even your own expectations
Star Elements program, inspired by the composition of stars themselves, comprising diverse elements that give unique qualities and illuminate for thousands of years
initiative aims to facilitate brilliance in our employees
Star Elements program encompasses a range of benefits, supporting our team across four pivotal facets of their lives and careers
Through Star Elements, our employees can fully realize their potential, both on personal and professional fronts

Fulltime

Machine Learning Research Engineer, Agents - Enterprise GenAI

Scale

Location:
United States , San Francisco ▼
New York

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 20, 2026

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