4 days ago
Remote, United States or Thousand Oaks, CA, USAStaff+
Base Salary
$144k - $195k/yr
Responsibilities
- Lead end-to-end design, development, and delivery of machine learning and GenAI solutions using Databricks, Spark, SQL, and Python.
- Architect large-scale data engineering and ML/GenAI initiatives across Databricks lakehouse platforms, distributed compute, and AWS, GCP, or Azure.
- Design batch and streaming data pipelines, data models, ML workflows, multi-agent architectures, reasoning workflows, tool integrations, and autonomous decision-making systems.
- Build scalable ETL/ELT data foundations in Databricks for downstream ML and GenAI use cases.
- Define evaluation, validation, governance, safety, hallucination-mitigation, and compliance frameworks for ML/GenAI systems.
- Partner with business stakeholders and product leaders to develop data-driven AI solutions, KPIs, and experimentation frameworks.
- Establish MLOps, LLMOps, DataOps, and DevOps practices including CI/CD, Databricks workflows, monitoring, observability, reproducibility, and cost optimization.
- Architect cloud-based data and AI platforms integrating Databricks Lakehouse, Spark, and cloud-native services.
- Lead A/B testing, prompt optimization, and data-driven experimentation.
- Mentor L4 and L5 engineers through design reviews, code reviews, and career guidance.
- Lead collaboration across data engineering, data science, platform engineering, and business teams.
Requirements
- Doctorate degree and 2 years of experience, or a master's degree and 4 years of experience, or a bachelor's degree and 6 years of experience, or an associate's degree and 10 years of experience, or a high school diploma/GED and 12 years of experience.
- Deep expertise in machine learning, deep learning, and Generative AI, including LLMs, transformers, embeddings, and fine-tuning techniques.
- Experience delivering production-grade ML/GenAI systems and designing scalable architectures with distributed systems and high-throughput pipelines.
- Expertise with MLflow, Kubeflow, Airflow, Docker, Kubernetes, and MLOps/LLMOps ecosystems.
- Strong system design, architecture, problem-solving, leadership, and initiative ownership skills.
- Experience with AWS, Azure, or GCP cloud platforms, cloud architecture, cost optimization, and cloud-native AI/ML services.
- Experience mentoring and guiding junior and mid-level engineers.
- Experience with Apache Spark, Hadoop, Databricks, SQL, Python, data pipelines, data modeling, and performance tuning.
- Proficiency with modern ML/AI frameworks such as PyTorch, TensorFlow, Hugging Face, or LangChain.
- Experience with evaluation and validation frameworks, human-in-the-loop systems, safety testing, monitoring, red-teaming, adversarial testing, and synthetic data generation.
- Experience with RAG architectures, vector databases, semantic search, vector search, NLP, embeddings, agentic AI frameworks, and knowledge-grounded AI systems.
- Understanding of statistical modeling, A/B testing, causal inference, Responsible AI, fairness, explainability, governance, and regulatory compliance.
- Experience tuning OLAP and OLTP systems and using workflow orchestration and distributed processing tools.
Benefits
- Comprehensive benefits including medical, dental, vision, life and disability insurance, flexible spending accounts, and a retirement and savings plan with company contributions.
- Discretionary annual bonus program or sales-based incentive plan for eligible field sales representatives.
- Stock-based long-term incentives.
- Award-winning time-off plans.
- Flexible work models where possible.
- Career development opportunities and work/life balance support.
Tech Stack
Apache AirflowApache HadoopApache SparkAWSAzureDatabricksDockerGoogle Cloud PlatformKubernetesMLflowPythonPyTorchSQLTensorFlow
Categories
Data EngineeringML Engineering
About Amgen
Amgen is a public biotechnology company that discovers, develops, manufactures, and sells biologic and biosimilar therapeutics for patients with serious diseases. Its portfolio and pipeline span oncology, cardiovascular disease, osteoporosis, inflammation, and rare diseases, marketed globally through direct sales and partnerships. Founded in 1980 and headquartered in Thousand Oaks, California (NASDAQ: AMGN), Amgen is a component of the Dow Jones Industrial Average and completed the acquisition of Horizon Therapeutics in 2023.