Role overview
Hybrid two weeks onsite a month in Westlake, TX
Our client is seeking a Machine Learning Engineer to build and optimize GenAI solutions on AWS, including RAG, prompt engineering, fine tuning, and LLM evaluation. The role will design and deploy Python-based APIs, integrate with ML models, and partner with data scientists to deliver scalable services. The engineer will develop data pipelines, manage deployments on SageMaker and containerized compute, and drive experiments to improve model performance. where we are at the forefront of developing cutting-edge AI solutions. We are seeking a passionate and skilled Machine Learning Engineer to design, implement, and enhance technical solutions for Gen AI applications. If you have a deep passion for data and application design, and thrive in a collaborative environment, we want to hear from you!
The Role: As a Machine Learning Engineer, you will be responsible for designing, implementing, and improving technical solutions for Gen AI solutions, including Retrieval-Augmented Generation (RAG), Prompt Engineering, Fine Tuning, ML model deployment, data pipelines, hosting, and API development. You will work closely with our data scientists to build AWS-based AI solutions, develop APIs, and integrate them with machine learning models.
Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.
Rate: $75.00 to $80.00/hr. w2
What you'll work on
- Design, implement, and improve GenAI solutions including RAG, prompt engineering, and fine tuning.
- Develop Python-based APIs and integrate with ML and LLM models in partnership with data scientists.
- Design and develop machine learning and deep learning systems using appropriate algorithms and frameworks.
- Design and develop machine learning and deep learning systems using ML algorithms and frameworks.
- Develop and integrate Python-based APIs using frameworks such as FastAPI or Flask.
- Work on Gen AI solutions with Large Language Models, utilizing frameworks like LangGraph, LangChain, and LlamaIndex.
- Deploy machine learning models on AWS services, including SageMaker, EC2, and EKS.
- Collaborate with data scientists to create models, perform statistical analysis, and optimize model performance.
- Run machine learning tests and experiments to evaluate and improve model outputs.
- Engage in prompt engineering and fine-tuning of models to enhance their capabilities.
- Evaluate LLM-generated content for quality and effectiveness.
- Deploy models on AWS SageMaker and manage compute on EC2/EKS.
- Build and maintain data pipelines and support analytics data hosting on Snowflake or RDS.
- Train and retrain models to optimize performance through tests and experiments.
What we're looking for
Bachelors Degree in computer science, engineering, or mathematics is highly desired, as well as demonstrated experience with cloud-based data platforms like Snowflake or RDS, or familiarity with statistical analysis and data-driven decision-making. Ideal candidate will have experience with either Large Language Models, LangGraph, LangChain, LlamaIndex, and / or experience developing Python based APIs, AWS.
Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team ([email protected], 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group’s use of these tools, including AI tools, as part of the application and hiring process.
Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.
W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.
Please be advised- If anyone reaches out to you about an open position connected with Eliassen Group, please confirm that they have an Eliassen.com email address and never provide personal or financial information to anyone who is not clearly associated with Eliassen Group. If you have any indication of fraudulent activity, please contact [email protected].