Machine Learning Engineer â LLM & AWS Integration
Machine Learning Engineer â LLM & AWS Integration
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Job Description
Dear All
We are looking for Machine Learning who is based out of Reston Virginia or Plano TX.
These roles are Hybrid Role with 3 Days a week to Reston / Plano Office
Machine Learning Engineer LLM & AWS Integration
Job Description:
About the Role
We are seeking a highly skilled and motivated Machine Learning Engineer to join our team and drive the development and optimization of AI solutions. This role is ideal for someone who thrives at the intersection of machine learning large language models (LLMs) and cloud infrastructure. You will collaborate closely with business stakeholders to design build and refine intelligent systems that leverage cutting-edge technologies.
Key Responsibilities
- Collaborate with business teams to understand requirements and translate them into ML models and prompt-based solutions.
- Design develop and fine-tune machine learning models particularly those involving LLMs and generative AI.
- Optimize and adapt prompt engineering strategies to improve model performance and relevance.
- Integrate and deploy models using AWS services including Bedrock S3 EC2 Lambda and others.
- Build and maintain scalable data pipelines and APIs to support ML workflows.
- Monitor model performance and iterate based on feedback and metrics.
- Stay current with advancements in AI/ML and cloud technologies to ensure our solutions remain cutting-edge.
Required Qualifications
- Bachelors or masters degree in computer science Data Science Engineering or a related field.
- 3 years of experience in machine learning data science or AI engineering.
- Hands-on experience with LLMs (e.g. OpenAI Anthropic Cohere) and prompt engineering.
- Strong proficiency in Python and ML libraries (e.g. TensorFlow PyTorch scikit-learn).
- Deep experience with AWS services especially Bedrock S3 EC2 and Lambda
- Familiarity with MLOps practices and tools for model deployment and monitoring.
- Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
- Strong programming skills in data analytics related languages such as Python R or JavaScript.
- Experience with AWS services such as S3 EC2 Lambda and particularly SageMaker for machine learning model deployment.
- Understanding of quantitative/statistical/ML/AI modeling methodologies.
- Experience in ML engineering including hands-on experience with Generative AI/LLMs.
- Working experience in EKS deployed application is a plus.
Preferred Qualifications
- Experience with fine-tuning or customizing foundation models.
- Knowledge of data privacy and security best practices in cloud environments.
- Familiarity with containerization (Docker) and orchestration (Kubernetes) is a plus.
Employment Type
Full Time
