Senior Machine Learning Operations Engineer
5 days ago
We are seeking a highly skilled Senior Machine Learning Operations Engineer to join our team at Jobot. As a key member of our organization, you will be responsible for designing, building, and deploying machine learning pipelines that drive business growth and innovation.
Key Responsibilities- Design and develop machine learning models and pipelines using Python and AWS ecosystem
- Collaborate with cross-functional teams to integrate machine learning solutions into our products and services
- Develop and maintain data pipelines using complex SQL, PySpark, Pandas, and similar frameworks
- Orchestrate complex workflows and data pipelines using Airflow or similar tools
- 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
- 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, preferably within the AWS ecosystem
- 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.
- Ability to design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc.
- Experience with MLOps practices such as automated model deployment, model performance monitoring, data drift detection, etc.
- 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, Data Observability tools and Data Governance tools
- Competitive base salary between $155k and $235k, depending on experience
- $12-14k in stock
- Bonus of 15-20%, depending on experience
- 100% remote work arrangement
- 401k with dollar-for-dollar match, up to 6% of eligible earnings (base, bonus)
- 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
- MacBook Pro and accompanying hardware to do great work
- 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 organizations
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