Machine Learning Engineer

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $109.5k - $208.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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AbbVie

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2013

🏥 Healthcare

💼 Consulting

🏭 Manufacturing

Healthcare • Consulting • Manufacturing

AbbVie is a global pharmaceutical company that discovers and delivers innovative medicines and solutions to enhance lives. With a focus on addressing the world's toughest health challenges, AbbVie operates in over 175 countries, providing a wide range of products across areas like immunology, oncology, neuroscience, and aesthetics. Committed to scientific innovation, AbbVie invests heavily in research and development, aiming to produce first-in-class medicines. The company also emphasizes workplace diversity, sustainability, and patient support initiatives, ensuring positive impact for both its patients and the broader community.

📋 Description

• Own small to medium components of machine learning systems from technical design through implementation and delivery • Translate technical requirements into maintainable code and deliver workstreams according to plan • Build and maintain data pipelines and feature engineering workflows for machine learning and AI solutions • Design, train, evaluate, and refine machine learning models • Implement ML solutions for production deployment as microservices, APIs, batch jobs, or streaming components • Support production monitoring by defining and implementing metrics for model performance, data drift, anomalies, and retraining triggers • Collaborate with Data Engineers, Software Engineers, Data Scientists, Product partners, and business stakeholders • Contribute to implementation decisions and technical tradeoffs using system design, data models, and technical artifacts • Follow governance, documentation, coding, and source control standards • Support teammates with day-to-day responsibilities • Document and communicate work progress, technical decisions, and outcomes to technical and non-technical audiences

🎯 Requirements

• Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Data Science, Engineering, Operations Research, or another quantitative field • 3+ years of practical experience building, evaluating, scaling, and deploying machine learning pipelines with Python • Strong Python programming skills and understanding of core computer science principles • Experience with Pandas and PySpark • Experience with scikit-learn, HuggingFace, TensorFlow/Keras, PyTorch, or MLlib • Experience with MLOps practices, including automated model deployment, model performance monitoring, and data drift detection • Working knowledge of SQL and relational data structures • Ability to design, train, and evaluate machine learning models using standard best practices • Familiarity with ETL, ELT, and stream processing • Experience with cloud environments, preferably AWS • Familiarity with APIs, microservices, Docker, and Kubernetes • Strong interpersonal, verbal, and written communication skills • Ability to work effectively in a remote environment using collaboration tools • Knowledge of recommender systems, fraud detection, personalization, and marketing science preferred • Experience managing and architecting AWS solutions preferred • Familiarity with LLMs, generative AI modalities, and production applications preferred • Familiarity with Snowflake, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, SageMaker, Datadog, PagerDuty, data cataloging, data observability, and data governance tools preferred

🏖️ Benefits

• Paid time off (vacation, holidays, sick) • Medical, dental, and vision insurance • 401(k) • Long-term incentive program eligibility • Remote work • Travel opportunity (10% of the time)