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Jobs via eFinancialCareers · 13 hours ago

GenAI ML/MLOps Engineering Lead (Remote)

Washington, DC

Full-time

Remote

Senior Level, Lead/Staff, Director/Executive

$108K/yr - $215K/yr

8+ years exp

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Responsibilities

Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions.

Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more.

Lead MLOps/LMOps platform development & automated pipelines focusing on deploying, monotoring and maintaining models in production environments; with model governance, cost and performance optimization.

Collaborate with cross-functional teams to integrate machine learning models into production systems.

Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures.

Work closely with members of technology teams in the development, and implementation of Enterprise AI platform.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

PythonMLOpsMachine Learning EngineeringBig DataElasticsearchSQLNoSQLApache AirflowApache SparkKafkaDatabricksMLflowContainerizationKubernetesCloud PlatformsCI/CDDistributed Systems ProgrammingAI/ML Solutions ArchitectureMicroservices ArchitectureData-Driven PipelinesOpen-Source ContributionsKaggle CompetitionsRAG PipelinesPrompt EngineeringGenerative AISageMakerVertex AI

Required

Bachelor's degree in Computer Science, Engineering, or a related field.

8+ years of progressive experience as in machine learning, data analytics or similar roles.

5 years of relevant experience with Writing production level, scalable code with Python (or scala)

MLOps/LLMOps, machine learning engineering, Big Data, or a related role.

Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow.

Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools.

Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience.

Preferred

2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions

Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions

6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases.

Experience with SageMaker and/or Vertex AI

Benefits

Health & Wellness: Health care coverage designed for the mind and body.

Flexible Downtime: Generous time off helps keep you energized for your time on.

Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference.