Senior Machine Learning Engineer

$155,000 - $235,000/Yr

Jobot - Minneapolis, MN

Full-time - Senior

Remote - Minneapolis, MN

Administrative and Support Services

About the position

As a Senior Machine Learning Engineer at our growing subsidiary of a large public company, you will play a pivotal role in developing and deploying machine learning models that drive our business forward. This position is fully remote, allowing you to work from the comfort of your home while collaborating with a talented team of engineers and data scientists. You will be responsible for building, evaluating, scaling, and deploying machine learning pipelines, primarily using Python and AWS. Your expertise will help us leverage advanced machine learning techniques to solve complex problems and enhance our product offerings. In this role, you will design, train, and evaluate machine learning models, ensuring adherence to best practices in model selection, validation, and performance assessment. You will also implement MLOps practices to automate model deployment and monitor performance, ensuring our models remain effective over time. Your experience with data pipelines and orchestration tools will be crucial as you work to integrate machine learning systems with our existing infrastructure. We are looking for someone with a strong foundation in computer science principles and practical experience in machine learning frameworks such as scikit-learn, TensorFlow, and PyTorch. You will collaborate closely with cross-functional teams to assess and implement new data tools, enhancing our machine learning stack and driving innovation within the company. This is an exciting opportunity to contribute to a dynamic team and make a significant impact on our business outcomes.

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.
• Develop batch and streaming pipelines using SQL, PySpark, and Pandas.
• Orchestrate complex workflows and data pipelines using tools like Airflow.
• Architect solutions on AWS or equivalent public cloud platforms.
• 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 machine learning frameworks and libraries such as scikit-learn, HuggingFace, PyTorch, TensorFlow/Keras, MLlib.
• Ability to design, train, and evaluate machine learning models with best practices in model selection and validation.
• Experience with MLOps practices including model performance monitoring and data drift detection.
• Experience with building data pipelines using complex SQL, PySpark, and Pandas.
• Experience with orchestrating workflows using tools like Airflow.
• Experience with architecting solutions on AWS or equivalent public cloud platforms.
• Experience with Git, CI/CD pipelines, Docker, and Kubernetes.
• Experience with developing data APIs and Microservices.

Nice-to-haves

• Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science.
• Knowledge of data mesh concepts.
• Experience with managing and architecting solutions on AWS.
• Familiarity with Snowflake, Monte Carlo, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, Sagemaker, DataDog, PagerDuty, Atlan, and Data Governance tools.

Benefits

• Competitive base salary between $155k and $235k, depending on experience.
• Generous stock grant.
• Bonus of 10-20%, depending on experience.
• 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.
• A modern productivity toolset including Slack, Miro, Loom, Lucid, Google Docs, Atlassian.
• Generous company discounts.
• Eligible for donation matching to over 1.5 million nonprofit organizations.