Senior Machine Learning Engineer

$155,000 - $235,000/Yr

Jobot - Denver, CO

posted 2 months ago

Full-time - Senior
Remote - Denver, CO
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, and scaling machine learning pipelines, ensuring that our models are not only effective but also efficient and scalable. Your expertise in Python and various machine learning frameworks will be crucial as you design, train, and evaluate models, adhering to best practices in model selection, validation, and performance assessment. In this role, you will leverage your experience with MLOps practices to automate model deployment and monitor performance, ensuring that our systems are robust and reliable. You will also be tasked with orchestrating complex workflows and data pipelines, utilizing tools like Airflow and SQL frameworks. Your ability to architect solutions on AWS or equivalent cloud platforms will be essential as we continue to enhance our machine learning capabilities. Additionally, you will have the opportunity to work with cutting-edge technologies, including Large Language Models and generative AI modalities, applying them in production environments to solve real-world problems. We are looking for a candidate who not only has a strong technical background but also possesses the ability to assess and implement new data tools to enhance our machine learning stack. You will be part of a dynamic team that values innovation and collaboration, and you will have the chance to contribute to exciting projects that impact our business and customers directly.

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.
  • 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 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 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 $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 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.
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