Senior Machine Learning Engineer

$155,000 - $205,000/Yr

Jobot - Washington, DC

Full-time - Senior

Remote - Washington, DC

Administrative and Support Services

About the position

We are seeking a talented Senior Machine Learning Engineer to join our growing subsidiary of a large public company. This position is fully remote, allowing you to work from the comfort of your home while contributing to exciting projects in the field of machine learning. As a Senior ML Engineer, you will play a crucial role in building, evaluating, scaling, and deploying machine learning pipelines. You will leverage your expertise in Python and various machine learning frameworks to design and implement robust models that adhere to best practices in the industry. In this role, you will be responsible for orchestrating complex workflows and data pipelines, utilizing tools such as Airflow and AWS. You will also engage in MLOps practices, ensuring automated model deployment and performance monitoring. Your experience with batch and streaming pipelines, as well as your ability to load test deployed models, will be essential in understanding performance breakpoints and enhancing our machine learning stack. We value innovation and collaboration, and you will have the opportunity to work with a modern productivity toolset, including Slack, Miro, and Google Docs. Additionally, you will be part of a fun team that participates in company events and has access to generous benefits, including a competitive salary, stock grants, and comprehensive insurance coverage.

Responsibilities

• Build, evaluate, scale, and deploy machine learning pipelines using Python, preferably within the AWS ecosystem.
• Design, train, and evaluate machine learning and AI models while adhering to best practices.
• Implement MLOps practices such as automated model deployment and performance monitoring.
• Orchestrate complex workflows and data pipelines using tools like Airflow.
• Develop data APIs, Microservices, and event-driven systems to integrate ML systems.
• Load test deployed models at scale to understand performance breakpoints.
• Assess and implement new data tools to enhance the machine learning stack.

Requirements

• Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, Operations Research, or other quantitative field.
• 5+ years of practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python.
• Strong programming skills in Python and understanding of core computer science principles.
• Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc.
• Experience with building batch and streaming pipelines using complex SQL, PySpark, Pandas, and similar frameworks.
• Experience with architecting solutions on AWS or equivalent public cloud platforms.
• Experience with Git, CI/CD pipelines, Docker, Kubernetes.

Nice-to-haves

• Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science.
• Knowledge of data mesh concepts.
• Familiarity with Snowflake, Monte Carlo, RDS, DynamoDB, Kafka, Fivetran, dbt, EMR, Sagemaker, DataDog, PagerDuty, Atlan, Data Observability tools and Data Governance tools.

Benefits

• Competitive base salary between $155k and $205k, depending on experience.
• Generous stock grant.
• Bonus of around 15%.
• 100% remote work.
• 401k with dollar for dollar match, up to 6% of eligible earnings.
• Comprehensive medical, dental, vision and life insurance.
• 17 paid holidays per year, including 3 floating holidays.
• Annual Paid Time Off (PTO), with separate sick days.
• 12 weeks paid Parental Leave.
• Caregiver Leave.
• Adoption and Surrogacy Assistance Plan.
• Flexible workplace accommodation.
• Fun team/company events at Sports games, concerts, etc.
• Tuition reimbursement.
• Ability to attend conferences.
• A MacBook Pro and accompanying hardware to do great work.
• A modern productivity toolset to get work done: Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more.
• Generous company discounts.
• Eligible for donation matching to over 1.5 million nonprofit organization.