Here for every sports story that matters.
Senior Machine Learning Operations Engineer
Location
United States
Posted
109 days ago
Salary
$140K - $150K / year
Seniority
Senior
Job Description
Senior Machine Learning Operations Engineer
The Athletic
• Design, build, and maintain machine learning model productionization infrastructure. These models will drive very visible product features at The Athletic, and your infrastructure is key to their success. • Work with the rest of the data science team to streamline model training, validation, and deployment. • Implement robust monitoring and alerting for model performance, drift, and data quality, ensuring our models remain accurate in production. • Cultivate an outstanding data science environment by championing best practices in ML Ops and evaluating and integrating new technologies into our data science stack.
Job Requirements
- 4-6 years of experience as a data scientist, data engineer, or machine learning engineer with a proven ability to build machine learning model pipelines and infrastructure.
- Strong working knowledge of Python and SQL to pull, transform, and otherwise deal with data in all of its forms.
- Proven experience with ML frameworks (e.g., scikit-learn, PyTorch) and cloud platforms (e.g., GCP, AWS, Azure).
- Hands-on experience with Docker, Kubernetes, and Airflow.
- Ability to drive projects with minimal guidance and prioritize high-impact work.
- Strong verbal and written communication skills with ability to build cross-functional relationships.
- Can explain sophisticated concepts to diverse audiences and craft compelling stories with data.
Benefits
- Highly competitive, employer-contributed medical, dental, vision, basic life and disability insurance plans.
- Savings accounts for medical, wellness, and childcare expenses.
- 401k retirement savings plan and employer match.
- Paid time off including paid sick leave, 12 paid holidays, 15 days of accrued vacation to start, and up to 20 weeks of Paid Parental Leave.
- Global benefits packages offer similar benefits and perks, competitive to the local market.
Related Guides
Related Job Pages
More Machine Learning Engineer Jobs
• educate the community of ML practitioners on accelerating training and inference workloads • publish technical blog posts • contribute documentation and code examples • speak at partner conferences • participate in or produce webinars • build and evangelize demos • lead GTM conversations with strategic partners
• Help build machine learning solutions used by millions leveraging cloud technologies • Work on integrating Hugging Face's open-source libraries with major cloud platforms or managed SaaS solutions • Bridging and integrating transformers/diffusers models with a different Cloud provider • Ensure models meet the expected performance • Design & Develop easy-to-use, secure, and robust Developer Experiences & APIs • Write technical documentation, examples and notebooks to demonstrate new features • Share & Advocate your work and results with the community
• Define and communicate the long-term vision for ML/AI applications and engineering, aligning with corporate strategy. • Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively. • Oversee design, development and deployment of enterprise-scale ML/AI solutions, inference pipelines, and respective technical roadmaps. • Ensure operational excellence in ML/LLM Ops, including automation, observability, and lifecycle management in partnership with the AIML platform engineering team. • Champion adoption of cutting-edge techniques (Deep learning, recommendation engine architecture, graph neural networks, causal inference, LLMs, RLs, etc). Drive responsible AI practices, model interpretability, and compliance with regulatory requirements. • Build and mentor a high-performing organization of managers and senior engineers. Foster a culture of continuous learning, experimentation, and engineering craftsmanship. • Establish standards for security, scalability, and architectural integrity across ML/AI systems. Implement robust governance for data privacy, ethical AI, and risk mitigation.
Applied Machine Learning Engineer – Expert
AllstateAllstate du Canada, compagnie d’assurance, est une cheffe de file dans le domaine des assurances automobile et habitation; elle offre à ses clients des produits et services de prévention et de protection qui conviennent à toutes les étapes de la vie. Au service des Canadiens depuis 1953, l’entreprise met tout en œuvre pour que non seulement ses clients, mais aussi ses employés soient en bonnes mains, comme en fait foi sa présence au palmarès des Employeurs de choix au Canada pendant neuf années de suite. Allstate du Canada tient à contribuer au mieux-être des communautés dans lesquelles elle exerce ses activités au moyen de partenariats avec des organismes caritatifs et de programmes misant sur la générosité de ses employés.
• Build secure, scalable, and high-performance microservices and applications using Java Spring Boot / Python • Design and maintain RESTful APIs and microservices architecture with asynchronous processing • Integrate and deploy Generative AI models into production environments • Optimize LLMs for specific use cases and implement RAG pipelines • Collaborate with platform consultants, product engineers, and digital product managers
