Senior Machine Learning Engineer

$155,000 - $235,000/Yr

Jobot - Indianapolis, IN

Full-time - Senior

Remote - Indianapolis, IN

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 leading the development and deployment of machine learning models and systems. This position is fully remote, allowing you to work from the comfort of your home while contributing to innovative projects that leverage cutting-edge technologies. You will be responsible for building, evaluating, and scaling machine learning pipelines, ensuring that they are robust and efficient. Your expertise in Python and familiarity with the AWS ecosystem will be crucial as you design and implement solutions that meet the needs of our clients and stakeholders. In this role, you will collaborate with cross-functional teams to understand business requirements and translate them into technical specifications. You will utilize your strong programming skills and knowledge of machine learning frameworks such as scikit-learn, PyTorch, and TensorFlow to develop models that drive business insights and enhance decision-making processes. Your ability to adhere to best practices in model selection, validation, and performance assessment will ensure that our machine learning solutions are both effective and reliable. Additionally, you will be involved in MLOps practices, focusing on automated model deployment and performance monitoring. Your experience with data pipelines, SQL, and orchestration tools like Airflow will enable you to manage complex workflows efficiently. As a leader in the team, you will also mentor junior engineers and contribute to the continuous improvement of our machine learning stack, exploring new tools and technologies to enhance our capabilities.

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 while adhering to best practices.
• Experience with MLOps practices such as automated model deployment and model performance monitoring.
• Experience with building batch and streaming pipelines using complex SQL, PySpark, and Pandas.
• Experience with orchestrating complex workflows and data pipelines 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, Microservices, and event-driven systems.

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, 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.
• A modern productivity toolset including Slack, Miro, Loom, Lucid, Google Docs, Atlassian, and more.
• Generous company discounts.
• Eligible for donation matching to over 1.5 million nonprofit organizations.