Senior Machine Learning Engineer (LLM Engineer)

Blue Orange Digital

11h•Remote

About The Position

Blue Orange is seeking an expert-level Machine Learning Engineer to address expanding opportunities, serving as a leader in LLM Engineering and Agentic AI. This senior role requires a candidate with extensive experience in the end-to-end ML/AI cycle, MLOps, LLMs, and a proven track record of designing and deploying complex, cloud-native data and ML/AI solutions. The candidate will mentor others and influence technical strategy.

Requirements

7+ years of industry experience as a hands-on practitioner in ML/AI, Data Science, or LLM/AI Engineering and proven experience with cloud offerings.
5+ years of experience with cloud platforms such as AWS.
Extensive experience with the end-to-end ML/AI cycle, MLOps, and LLMs.
Expertise in advanced machine learning techniques, data analytics, and feature engineering.
Experience with NLP and LLM-based technologies and frameworks.
Mastery of Python and advanced proficiency in SQL.
Expertise in 3–5 major cloud and data platforms and exposure to all (AWS, GCP, Azure, Snowflake, and Databricks).
Self-driven and autonomous with excellent problem-solving skills and critical thinking.
Excellent verbal and written communication skills to collaborate with technical and non-technical stakeholders effectively.
Proven ability to lead customer engagement and influence technical direction in a consulting environment.
Bachelor's degree or higher in Computer Science or a related field.

Nice To Haves

Advanced degree in a relevant field.
Publications in relevant AI/ML communities and journals.
Experience fine-tuning LLMs and deploying them (e.g., using MLFlow) a plus.

Responsibilities

Lead the design and productionization of machine learning, ML ops, traditional AI, LLMs, and agentic AI solutions into scalable, product-driven applications, serving as a technical expert.
Drive the implementation of complex application integrations to leverage and deploy machine learning, ML ops, traditional AI, LLMs, and agentic AI products.
Define and implement architectural solutions that ensure the delivery speed and scalability of product and data pipelines.
Lead the adoption of managed and serverless cloud offerings to create performant and scalable cloud-native application solutions and data pipelines.
Lead the implementation of advanced machine learning models including regression, classification, Bayesian methods, Retrieval-Augmented Generation (RAG), and advanced Agentic AI architectures.
Serve as a technical leader to integrate prompt engineering and RAG components into production systems, ensuring seamless and robust deployment.
Serve as a key resource in client-facing consulting, driving customer engagement and influencing technical solutions for clients.
Stay up to date with the latest advancements in prompt engineering, RAG, data science, machine learning, and AI technologies, exploring innovative approaches to enhance machine learning, ML ops, traditional AI, LLMs, and agentic AI capabilities across the organization.