Sr Machine Learning Engineer -AI/ML- US Remote

Remote in Jacksonville, FL, US • Posted 4 days ago • Updated 5 hours ago

Full Time

On-site

USD 164,029.00 per year

Fitment

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Job Details

Skills

Information Systems
Training
Optimization
Evaluation
Promotions
SDK
Stacks Blockchain
Research
Kubernetes
UI
Workflow
Statistics
GPU
CPU
SLA
Real-time
Analytics
Continuous Improvement
Encryption
Collaboration
Partnership
Privacy
Regulatory Compliance
Apache Velocity
Data Analysis
Ideation
Scalability
KPI
Enterprise Software
Algorithms
Regression Analysis
Clustering
Time Series
Deep Learning
SaaS
PaaS
Vector Databases
Prompt Engineering
LangChain
Semantics
Python
Java
Docker
Cloud Computing
DevOps
Machine Learning Operations (ML Ops)
GitHub
Amazon SageMaker
Business Cases
NPV
Stakeholder Management
Biotechnology
Pharmaceutics
Thought Leadership
Data Science
Agile
SAFE
Project Delivery
Computer Science
Generative Artificial Intelligence (AI)
Amazon Web Services
Microsoft Azure
Artificial Intelligence
Google Cloud Platform
Google Cloud
Machine Learning (ML)
Soft Skills
Analytical Skill
Communication
Virtual Team
Motivation
Management
FOCUS
Organized
Attention To Detail
Presentations
Public Speaking

Summary

Career Category
Information Systems
Job Description

ABOUT THE ROLE

Role Description:

We are seeking a Sr Machine Learning Engineer-Amgen's senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms. Sitting at the intersection of engineering excellence and data-science enablement, you will design the core services, infrastructure and governance controls that allow hundreds of practitioners to prototype, deploy and monitor models-classical ML, deep learning and LLMs-securely and cost-effectively. Acting as a "player-coach," you will establish platform strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI developer experience.

Roles & Responsibilities:

Engineer end-to-end ML pipelines-data ingestion, feature engineering, training, hyper-parameter optimization, evaluation, registration and automated promotion-using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks.
Harden research code into production-grade micro-services, packaging models in Docker/Kubernetes and exposing secure REST, gRPC or event-driven APIs for consumption by downstream applications.
Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency.
Optimize performance and cost at scale-selecting appropriate algorithms (gradient-boosted trees, transformers, time-series models, classical statistics), applying quantization/pruning, and tuning GPU/CPU auto-scaling policies to meet strict SLA targets.
Instrument comprehensive observability-real-time metrics, distributed tracing, drift & bias detection and user-behavior analytics-enabling rapid diagnosis and continuous improvement of live models and applications.
Embed security and responsible-AI controls (data encryption, access policies, lineage tracking, explainability and bias monitoring) in partnership with Security, Privacy and Compliance teams.
Contribute reusable platform components-feature stores, model registries, experiment-tracking libraries-and evangelize best practices that raise engineering velocity across squads.
Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
Partner with data scientists to prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.

Must-Have Skills:

3-5 years in AI/ML and enterprise software.
Comprehensive command of machine-learning algorithms-regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques-with the judgment to choose, tune and operationalize the right method for a given business problem.
Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, Semantic Kernel).
Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, Azure or Google Cloud Platform) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
Strong business-case skills-able to model TCO vs. NPV and present trade-offs to executives.
Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.

Good-to-Have Skills:

Experience in Biotechnology or pharma industry is a big plus
Published thought-leadership or conference talks on enterprise GenAI adoption.
Master's degree in computer science and or Data Science
Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

Master's degree with 8 + years of experience in Computer Science, IT or related field

Bachelor's degree with 10 + years of experience in Computer Science, IT or related field
Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.

Soft Skills:

Excellent analytical and troubleshooting skills.
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation.
Ability to manage multiple priorities successfully.
Team-oriented, with a focus on achieving team goals.
Ability to learn quickly, be organized and detail oriented.
Strong presentation and public speaking skills.

Salary Range
164,029.00 USD - 209,103.00 USD

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 80180362
Position Id: ac4ce754cf7e34010c6343ae8f44b3f4
Posted 4 days ago

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Sr Machine Learning Engineer -AI/ML- US Remote

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