Machine Learning Engineer, Data Operations

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $151.5k - $244.2k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 0%

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Eli Lilly and Company

WebsiteLinkedInAll Job Openings

10,000+ employees

💊 Pharmaceuticals

🏥 Healthcare

🧬 Biotechnology

💰 $6.5M Post-IPO Debt - Eli Lilly on 2024-02

Pharmaceuticals • Healthcare • Biotechnology

Eli Lilly and Company is a multinational pharmaceutical company that researches, develops, manufactures, and markets prescription medicines across multiple therapeutic areas including diabetes, oncology, immunology, neuroscience, and pain. Headquartered in Indianapolis, Indiana, Lilly is known for its extensive R&D, clinical development, and global commercialization of biologic and small-molecule drugs. The company focuses on drug discovery, clinical trials, regulatory approvals, and large-scale pharmaceutical manufacturing and distribution.

📋 Description

• Move trained models from research and experimentation into production across development, staging, and production environments • Package, version, and promote models across AWS, Azure, GCP, and on-premises or hybrid infrastructure • Build and operate scalable batch, real-time, and streaming inference services and APIs • Design and maintain containerized Kubernetes model-serving infrastructure with autoscaling, versioned rollouts, and rollback • Integrate models into researcher-facing tools and enterprise systems • Design, build, and maintain secure batch, CDC, and streaming data pipelines • Build embedding, vectorization, and feature pipelines for ML and LLM applications • Implement scalable storage and retrieval for structured and unstructured scientific data • Operate automated data-readiness and quality-monitoring workflows • Detect anomalies, outliers, missing values, illegal characters, structural issues, and schema drift • Author, review, and validate model cards and model documentation • Automate model validation and evaluation, including metric reproduction, calibration, and acceptance-criteria checks • Implement production monitoring for model, data, and service health, with alerting and proactive remediation • Define acceptance criteria, audit trails, reproducible checks, and operational metrics • Design and develop robust, scalable, and secure software solutions • Build and maintain REST and GraphQL microservices and APIs • Implement infrastructure-as-code and CI/CD pipelines using test-driven development • Troubleshoot distributed systems and complex issues across the model, data, and serving stack • Collaborate with Lilly Research Labs, Data Science, AI/ML, IT Operations, and external collaborators • Contribute documentation, data dictionaries, runbooks, platform adoption, and internal end-user support

🎯 Requirements

• Ph.D. in Computer Science or a related computational field • Hands-on experience in software engineering and architecture, with a proven track record of delivering complex, cross-functional solutions • Proficiency in a systems or object-oriented language: Go, Rust, Java, or C++ • Proficiency in Python and/or JavaScript • Hands-on experience deploying to containers, serverless, Kubernetes, and other hosting targets • Experience deploying and serving machine learning models in production, including packaging, versioning, and promotion across environments • Experience building data pipelines and working with relational and non-relational data stores, such as PostgreSQL, MySQL, and MongoDB • Solid understanding of HTTP and RESTful APIs • Experience using CI tools to automatically test and CD tools to automatically deploy updates • Experience applying test-driven development to prevent feature regression • Experience applying systems-engineering concepts to distributed systems with high throughput and availability requirements • Preferred: Experience integrating AI/ML models into production with a focus on scalability, performance, and reliability (MLOps) • Preferred: Familiarity with MLOps and model-serving tooling, such as MLflow, Kubeflow, and JFrog Artifactory • Preferred: Experience with model validation, evaluation, and model-card and documentation practices for model governance • Preferred: Experience implementing data-quality, anomaly-detection, or schema-drift monitoring • Preferred: Familiarity with streaming and CDC tooling, such as Kafka, Kafka Streams, and Spark Streaming, and big-data processing with Spark • Preferred: Familiarity with LLM application patterns, including retrieval-augmented generation, tool-calling, and multi-agent orchestration, and inference optimization • Preferred: Experience with infrastructure-as-code, Terraform, service mesh, and cloud-native monitoring and observability • Preferred: Exposure to drug discovery, life sciences, or healthcare data and workflows • Preferred: Experience contributing to federated or collaborative ML and data initiatives across organizations

🏖️ Benefits

• Company bonus depending, in part, on company and individual performance • Company-sponsored 401(k) • Pension • Vacation benefits • Medical, dental, vision, and prescription drug benefits • Flexible benefits, including healthcare and/or dependent day care flexible spending accounts • Life insurance and death benefits • Time off and leave of absence benefits • Well-being benefits, including employee assistance program, fitness benefits, and employee clubs and activities