Machine Learning Engineer

Job not on LinkedIn

🕒 3 days 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 high-quality, maintainable code and deliver workstreams according to plan • Build and maintain data pipelines and feature engineering workflows to support machine learning and AI solutions • Design, train, evaluate, and refine machine learning models with minimal supervision, applying sound statistical and engineering practices • Implement ML solutions that can be deployed into production environments as microservices, APIs, batch jobs, or streaming components • Support production monitoring efforts by helping define and implement metrics for model performance, data drift, anomalies, and retraining triggers • Collaborate with Data Engineers, Software Engineers, Data Scientists, Product partners, and business stakeholders to deliver project objectives • Understand system design, data models, and technical artifacts well enough to contribute to implementation decisions and tradeoffs • Follow governance, documentation, coding, and source control standards consistently • Demonstrate flexibility and proactively support teammates with day-to-day responsibilities as needed • Clearly 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 other quantitative field • 3+ years of practical experience building, evaluating, scaling, and deploying machine learning pipelines with Python • Strong programming skills in Python and solid understanding of core computer science principles • Experience with data manipulation frameworks such as Pandas and PySpark • Experience with machine learning libraries such as scikit-learn, HuggingFace, TensorFlow/Keras, PyTorch, or MLlib • Experience with MLOps practices such as automated model deployment, model performance monitoring, data drift detection • Working knowledge of SQL and relational data structures • Familiarity with batch and streaming data pipeline concepts such as ETL, ELT, and stream processing • Experience working with cloud environments, preferably AWS • Familiarity with technologies such as APIs, microservices, Docker, and Kubernetes • Strong interpersonal, verbal, and written communication skills • Ability to work effectively in a remote environment using collaboration tools

🏖️ Benefits

• Paid time off (vacation, holidays, sick) • Medical/dental/vision insurance • 401(k) • Long-term incentive programs