

AI/ML Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include proficiency in Python, Azure ecosystem, MLOps, and experience in generative AI. A Bachelor's degree or 7 years of software development experience is required.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
640
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ποΈ - Date discovered
July 30, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Dataflow #PyTorch #Model Evaluation #Snowflake #Langchain #Reinforcement Learning #Azure DevOps #Databases #Data Science #Observability #Azure #Kubernetes #AzureML #Libraries #"ETL (Extract #Transform #Load)" #Deployment #Documentation #ML (Machine Learning) #Computer Science #GitHub #Snowpark #Transformers #Python #Scala #Microsoft Azure #Automated Testing #Streamlit #Docker #DevOps #MLflow #Monitoring #Hugging Face #AI (Artificial Intelligence) #Agile
Role description
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ABOUT THE ROLE:
β’ The Senior Machine Learning Engineer - Generative AI is responsible for designing, developing, and operationalizing advanced Machine Learning (ML) and generative AI solutions, including Retrieval-Augmented Generation (RAG) and image generation systems. This role focuses on leveraging large language models (LLMs), prompt engineering, advanced LLM techniques and architectures, and MLOps best practices to build scalable, secure, and high-performing AI applications. The incumbent will work closely with cross-functional teams to integrate Microsoft Azure, Snowflake, and other emerging technologies into production solutions that drive innovation and business value.
WHAT THE ROLE WILL DO:
β’ Design and implement generative AI systems, including RAG pipelines and applications using Azure OpenAI, Azure Cognitive Search, Snowflake Cortex, and other available generative AI systems.
β’ Develop and fine-tune language models (LLMs and SLMs) and associated applications using techniques such as supervised fine-tuning, reinforcement learning with human feedback (RLHF), and prompt tuning.
β’ Engineer effective prompts and retrieval strategies to optimize LLM performance and relevance.
β’ Build and maintain CI/CD pipelines for generative AI work- and data-flows.
β’ Integrate Snowflake's native ML capabilities (e.g., Snowpark, Snowflake ML, Cortex) for data preparation, feature engineering, and inference.
β’ Conduct hyperparameter tuning and model evaluation using tools like AzureML, Optuna, and Weights & Biases.
β’ Implement observability and monitoring for LLMs, including hallucination detection, drift monitoring, and feedback loops.
β’ Collaborate with data scientists, software engineers, and product teams to translate business needs into scalable AI solutions.
β’ Maintain documentation for model development, deployment workflows, and prompt libraries.
β’ Stay current with advancements in generative AI, foundation models, and RAG architectures.
WHAT THE INCUMBENT WILL NEED:
β’ Education
β’ Required
β’ Bachelor's Degree in Computer Science or Computer Engineering or in lieu of a degree, at least 7 years of experience in software development
β’ Preferred
Master's in AI, Machine Learning, or Data Science.
β’ Skills and Experience
Grade: #
Required
Preferred
Knowledge & Experience
β’ 4-6 years of experience in ML, MLOps, and/or software development, with at least 1 year in generative AI or LLMs
β’ In-depth knowledge of software development life cycle (SDLC) methodologies and practices, particularly MLOps and DevOps
β’ Proficiency in Python and experience with libraries such as LangChain, Transformers, Hugging Face, and PyTorch.
β’ Experience with Microsoft Azure ecosystem: Azure OpenAI, AzureML, Azure Cognitive Search, Azure DevOps.
β’ Experience with Snowflake ecosystem: Snowpark, Snowflake ML, Cortex, and Streamlit in Snowflake.
β’ Strong understanding of RAG architectures, vector databases (e.g. FAISS, Azure Cognitive Search), and embedding models.
β’ Experience with prompt engineering, few-shot learning, and fine-tuning LLMs.
β’ Familiarity with MLOps tools: MLflow, Docker, Kubernetes, and GitHub Actions.
β’ Knowledge of CI/CD, automated testing, and model monitoring in production environments.
β’ Experience with hyperparameter tuning frameworks (e.g., Optuna, Ray Tune).
β’ Strong communication and documentation skills.
β’ Experience with reinforcement learning (e.g., RLHF), synthetic data generation, or human-in-the-loop systems
β’ Familiarity with Snowflake Native Apps and secure data sharing.
β’ Contributions to open-source LLM or RAG projects
β’ Experience building and maintaining Small Language Models (SLM) and applications thereof
β’ Experience in software development in an agile environment
β’ Ability to communicate effectively with non-technical users
Impellam Group and its brands are equal-opportunity employers committed to diversity and inclusion. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, pregnancy or maternity, national origin, age, disability, veteran status, or any other factor determined to be unlawful under applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application, interview process, pre-employment activity, and the performance of crucial job functions.
If you require additional disability considerations, modifications, or adjustments please let us know by contacting HR-InfoImpellamNA@impellam.com or fill out this form to request accommodations.