Senior Machine Learning Engineer

🕒 August 27

🇺🇸 United States – Remote

💵 $156.2k - $211.3k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 39%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Amgen

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1980

🏥 Healthcare

🧬 Biotechnology

💊 Pharmaceuticals

💰 $28.5G Post-IPO Debt on 2022-12

Healthcare • Biotechnology • Pharmaceuticals

Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.

📋 Description

• Contribute to the development of scalable machine learning platforms and workflows enabling scientists and researchers to build, deploy, and manage AI/ML models • Work with engineers, data scientists, and domain experts to productionize machine learning solutions supporting drug discovery and development • Deliver AI and ML-enabled applications and platforms, including classical ML, natural language processing, protein language models, and large language models • Develop and maintain ML platform capabilities, including data pipelines, feature engineering, model training, evaluation and deployment pipelines, experiment tracking, model registries, performance evaluation and monitoring • Implement AI and MLOps best practices, including CI/CD, cloud infrastructure as code, monitoring, traceability, and reproducibility • Collaborate with cross-functional teams to transition experimentation standards and outcomes into production-grade enterprise solutions • Build and maintain scalable, efficient productionized MLOps solutions on cloud platforms • Develop and deliver training content and knowledge articles to educate scientists on model lifecycle management best practices

🎯 Requirements

• Doctorate degree OR Master’s degree and 2 years of relevant experience in Computer Science, IT, or related field OR Bachelor’s degree and 4 years of relevant experience in Computer Science, IT, or related field OR Associate’s degree and 8 years of relevant experience in Computer Science, IT, or related field OR High school diploma / GED and 10 years of relevant experience in Computer Science, IT, or related field • Software programming (Python, version control, test driven development) • Experience with cloud technologies (AWS preferred, Databricks) • Hands-on experience with AI/ML model training and serving • Sponsorship for this role is not guaranteed • Preferred: Experience with deployment and maintenance of AI/ML models in production • Preferred: Substantial experience with cloud technologies and platforms, such as Databricks, AWS, or Azure • Preferred: Experience with AI and MLOps frameworks and tools (MLflow, Kubeflow, Weights & Biases, Terraform, etc.) • Preferred: Experience with containerization (Docker, Kubernetes) • Preferred: Familiarity with distributed data processing (e.g., Spark) • Preferred: Familiarity with data science libraries (scikit-learn, TensorFlow, PyTorch, LangChain) • Preferred: Experience with graph databases • Excellent critical-thinking and problem-solving skills • Strong communication and collaboration skills • Demonstrated presentation skills • Self-motivated, independent ownership and leadership skills

🏖️ Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions • Group medical, dental and vision coverage • Life and disability insurance • Flexible spending accounts • Discretionary annual bonus program • Stock-based long-term incentives • Award-winning time-off plans • Flexible work models where possible • Career development opportunities • Financial plans with opportunities to save towards retirement or other goals • Work/life balance support