Senior Machine Learning Engineer (Temporary)
About The Position
Brooks is embarking on an exciting journey to harness our data assets across a wide range of job functions—including product innovation, marketing, supply chain, customer experience, and various corporate areas such as HR, Finance, IT, and Legal. Our goal is to build and scale the data science and Machine Learning capabilities to support every corner of our operations and the communities we serve. At Brooks, we collaborate and are super curious to explore the "art of the possible" with data and technology in service to our runners and the communities we serve. As a Senior Machine Learning (ML) Engineer, you will work closely with Data Engineers, Architects and Business stakeholders to undertake research and transition models into scalable production code. We’re looking for someone who embraces ML Engineering best practices, developing high-performance, reusable code and infrastructure. This is an 8-month full-time temporary role.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, Mathematics, or a related field or equivalent combination of education and/or experience.
- 7+ years of experience in Machine Learning, Data Engineering, and Data Architecture.
- 2+ years of hands-on experience in GenAI, NLP and Agentic AI building production grade systems.
- Extensive experience in retail and applied consumer product industries is highly valued.
- Strong proficiency in Python (preferred), Java, or R and SQL.
- Deep knowledge of frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, and LangChain.
- Hands-on experience with AWS (Bedrock, SageMaker), Azure (Databricks), or GCP (Vertex AI, BigQuery).
- Solid understanding of probability, statistics & ML algorithms.
- Excellent verbal and written communication skills, with the ability to break down technical topics for non-technical audiences.
- Actively works to learn new skills to stay current with changing technologies and industry trends
- Ability to work cross-functionally with Platform teams on enterprise initiatives and engage regularly with other architecture, security, and infrastructure teams
- Ability to multi-task and manage multiple priorities concurrently
- Embraces and lives Brooks values!
Responsibilities
- Design, build, and test machine learning models and algorithms, within established architectures like Transformers (BERT), Deep Learning (CNNs), and Large Language Models (LLMs).
- Conduct exploratory data analysis and drive end-to-end data science solutions for diverse business needs.
- Lead Al strategy and implementation across cutting-edge Generative AI and RAG (Retrieval-Augmented Generation) solutions.
- Undertake feature engineering and evaluate models for accuracy and performance.
- Deploy models for customers and transition them to production through MLOps, ensuring smooth integration with existing systems.
- Implement containerization and orchestration using Docker and Kubernetes for scalable model serving.
- Establish ongoing retraining, monitoring, and optimization of machine learning systems to maintain top performance and accuracy.
- Leverage Infrastructure as Code (IaC) tools like Terraform to manage AI/ML infrastructure.
- Work cross-functionally with Architects, Product Managers, Data Engineering, and Business Intelligence teams to deliver integrated solutions.
- Actively mentor and coach developers and junior designers across multiple teams.
Benefits
- medical
- dental
- vision
- HSA and employer contribution
- FSA
- family & fertility assistance
- 401K Savings Plan and match
- employee assistance program
- transportation assistance
- Eleven paid holidays
- paid sick
- product discounts
- employee recognition
- fitness discounts
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What This Job Offers
Job Type
Full-time
Career Level
Senior
