Sr. Manager, Machine Learning Job at Roku (Bengaluru)

Sr Machine Learning Engineer

Let’s do this. Let’s change the world. We are looking for a highly motivated exp...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Hands-on experience with AWS, Databricks, Apache Spark, PySpark, SparkSQL, Python, and SQL for large-scale data engineering
Strong proficiency in workflow orchestration, Spark performance tuning, and scalable batch and streaming data pipeline development
Experience with real-time data processing and integration using Apache Kafka, Debezium, or similar streaming technologies
Hands-on experience with MLOps tools and practices, including MLflow, model serving, feature stores, experiment tracking, deployment, and lifecycle management
Experience with GenAI engineering practices, including prompt engineering, LLM evaluation, AI observability, agentic workflows, and knowledge graphs
Ability to design and develop APIs or service interfaces for data, ML, and GenAI application integration
Experience with Agile/SAFe delivery models, DevOps practices, CI/CD concepts, and cross-functional team collaboration
Strong analytical, problem-solving, debugging, communication, and teamwork skills
Ability to quickly learn, adapt, and apply emerging technologies across data, ML, and AI engineering
Doctorate degree / Master's degree / Bachelor's degree and 8 to 13 years of experience years of experience in Computer Science, IT or related field

Job Responsibility

Design, deploy, monitor, and optimize production-grade ML and Generative AI applications for AI-enabled manufacturing solutions
Define technical architecture, engineering standards, and best practices across data engineering, ML, GenAI, analytics, and platform capabilities
Partner with business stakeholders, product owners, and cross-functional teams to translate manufacturing challenges into secure, scalable, production-ready AI and data solutions
Design, develop, and maintain complex ETL/ELT pipelines in Databricks using PySpark, Scala, and SQL for large-scale structured and unstructured data processing
Build efficient ingestion, transformation, migration, and deployment pipelines across databases, APIs, logs, event streams, images, PDFs, documents, and third-party platforms
Design and implement GenAI solutions including RAG, embeddings, vector databases, agentic workflows, tool-calling systems, LLM orchestration, serving optimization, knowledge graphs, and metadata-driven retrieval
Build GenAI applications using frameworks and platforms such as LangChain, LangGraph, LlamaIndex, DSPy, OpenAI APIs, Amazon Bedrock, or equivalent technologies
Develop evaluation and observability frameworks to monitor model quality, hallucination rates, drift, retrieval effectiveness, latency, token usage, cost, reliability, operational health, and business impact
Build and maintain MLOps and LLMOps capabilities, including experiment tracking, model registry, prompt management, versioning, CI/CD, automated testing, deployment automation, monitoring, governance, and release controls
Design scalable data quality, validation, security, privacy, access control, logging, governance, and interoperability capabilities across hybrid cloud environments

Fulltime

Sr Machine Learning Engineer, Pricing

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pri...

Location

United States , New York; Seattle; San Francisco; Sunnyvale

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions
Proficiency in programming languages such as Python, Scala, Java, or Go
Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization)

Job Responsibility

Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
Collaborate with the team leads to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Sr. Machine Learning Engineer – Context Engineering

GEICO is seeking an experienced Sr. Staff Machine Learning Engineer to join our ...

Location

United States , New York City; Palo Alto; Chevy Chase

Salary:

115000.00 - 230000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

5+ years of experience designing and building AIML platform and systems utilizing components such as vectordb (e.g. Qdrant, Milvus, etc.), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgres sql), knowledge graph (e.g. neo4j), workflow orchestration (e.g. Airflow, Temporal)
Proficient in Python, Java and similar general-purpose programming languages
3+ years’ experience managing end-to-end software development life cycle (e.g. CICD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for backend systems and APIs
2+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Job Responsibility

Own development of key platform components that power end-to-end GenAI agentic workflows. Examples include knowledge curation & management, search, context management, workflow orchestration, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs for high impact business use cases. Establish pragmatic visions & roadmaps that balance business outcome, product release timelines and engineering excellence
Contribute to the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Lead a small team of engineers for feature & system implementation. Troubleshoot and resolve complex software issues, ensuring optimal platform performance and reliability
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company

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

Sr. Machine Learning Engineer

Our Machine Learning Team is developing next-generation AI capabilities for High...

Location

United States , Seattle

Salary:

171000.00 - 254100.00 USD / Year

Highspot

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
5+ years of experience in developing and deploying machine learning models and systems
Strong proficiency in at least one programming language (Python, Java, C++, etc.) and experience with machine learning libraries (TensorFlow, Keras, PyTorch, etc.)
In-depth understanding of machine learning concepts, such as supervised and unsupervised learning, deep learning, and natural language processing
Experience with data processing tools and technologies, such as Spark, Flink, Hadoop, and SQL databases
Strong problem-solving skills and ability to analyze complex data sets
Excellent communication skills and ability to articulate complex technical concepts to non-technical stakeholders
An entrepreneurial spirit: you’re agile, creative, resourceful, and tenacious as you solve problems and achieve team and company goals
Comfortable with modern open source technologies and tools
Passion to learn new technologies and infrastructure

Job Responsibility

Collaborate with product and data science teams to identify opportunities that drive customer values, and define machine learning requirements, lead the development and deployment of machine learning solutions and applications, while ensuring scalability, reliability, and maintainability
Develop and maintain a robust machine learning platform that enables the efficient deployment and management of machine learning models across our product offerings
Stay up-to-date with the latest machine learning research and trends, and apply them to our product offerings, while mentoring and collaborating with junior team members to improve their technical skills
Partner cross-functionally across all of Highspot’s feature engineering crews, as well as with QA/DevOps/Site-Reliability

What we offer

Comprehensive medical, dental, vision, disability, and life benefits
Health Savings Account (HSA) with employer contribution
401(k) Matching with immediate vesting on employer match
Flexible PTO
8 paid holidays and 5 paid days for Annual Holiday Week
Quarterly Recharge Fridays (paid days off for mental health recharge)
18 weeks paid parental leave
Access to Coaches and Therapists through Modern Health
2 volunteer days per year
Commuting benefits

Fulltime

Sr Machine Learning Engineer -AI/ML- US Remote

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

Location

United States , Jacksonville

Salary:

164029.00 - 209103.00 USD / Year

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—with the judgment to choose, tune and operationalize the right method for a given business problem
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
containerization (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 optimization, 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
Optimize performance and cost at scale—selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantization/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-behavior 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 evangelize 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

Fulltime

New

Sr. Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...

Location

United States , New York; San Francisco; San Jose; Cambridge; McLean

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI
Use programming languages like Python, Scala, or Java

What we offer

performance based incentive compensation
cash bonus(es)
long term incentives (LTI)
health, financial and other benefits

Fulltime

Sr Staff Machine Learning Engineer (ADEM)

The ADEM engineering team is the engine of innovation at Palo Alto Networks. We ...

Location

United States , Santa Clara

Salary:

147000.00 - 237500.00 USD / Year

Palo Alto Networks

Expiration Date

Until further notice

Requirements

6+ years of software engineering experience, with a significant portion dedicated to designing and operating complex, resource-constrained client-side or endpoint software in a large-scale deployment
As a leader in engineering efficiency, you must be an expert in leveraging AI-powered development tools—including Claude Code, Cursor, Windsurf, and GitHub Copilot—to radically accelerate the SDLC and automate complex refactoring and testing workflows
Proven track record of architecting and shipping production-quality software for multiple operating systems (Windows, macOS, Linux) with a deep understanding of OS internals, networking stacks (L3-L7), and system performance tuning
Coding Rust, or Go (Golang) for high-performance client development is required
BS/MS/PhD in Computer Science or a related technical field, or equivalent high-level professional experience.

Job Responsibility

Define the long-term architectural vision for the ADEM Agent across Linux, Windows, macOS, and mobile platforms, ensuring robust performance, minimal resource consumption
Lead the 'Design Review Board' for all Agent-side features, ensuring all components adhere to Secure AI by Design, operate with high-availability patterns in diverse OS environments, and maintain a low CPU/memory footprint
Drive the evolution of the Agent's telemetry collection and processing pipeline, optimizing for low-latency, encrypted data transfer and ensuring resilience in low-bandwidth or disconnected environments
Partner with Product Management, Core Infrastructure, and Security teams to translate ambiguous business requirements into robust, high-performance technical specifications for the client software
Act as a force multiplier by mentoring Staff and Senior engineers, fostering a culture of rigorous platform-specific testing, high code quality, and proactive technical debt management within the Agent codebase
Serve as the ultimate technical escalation point for complex, systemic production issues related to endpoint stability or performance, leading post-mortems that drive permanent architectural improvements in the Agent

What we offer

restricted stock units
bonus

Fulltime

Sr Engineer, Machine Learning Engineering

The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capab...

Location

United States , Bellevue; Atlanta; Overland Park; Herndon

Salary:

127000.00 - 229100.00 USD / Year

T-Mobile

Expiration Date

Until further notice

Requirements

Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments
5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions
5+ years of experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications
2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands-on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face
At least 18 years of age
Legally authorized to work in the United States

Job Responsibility

Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance
Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications
Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement
Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness
Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies

What we offer

annual stock grant
employee stock purchase plan
401(k)
free, year-round money coaches
medical insurance
dental insurance
vision insurance
flexible spending account
paid time off
up to 12 paid holidays

Fulltime

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Sr. Manager, Machine Learning

Job Description

Job Responsibility

Requirements

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