Job Title: Cloud Infrastructure/AI/ML Engineer Location: Hybrid (Waltham, MA) (Local Only) Work Authorization: USC/GC/GCEAD/H4EAD/OPT Pay rate: $55-$60/hr on C2C Job Description : 12+ month extendable Contract role. Hybrid weekly onsite work required in Waltham, MA. -(3-4 days/week). Role focuses on providing infrastructure solutions to enable AI/ML model development and applications. The position will require pipeline execution, environment management, AI/ML model development/deployment, and management of data for various bioinformatics workflows. Lenox Executive Search is seeking an experienced Cloud Infrastructure/AI/ML Engineer to fill an 12+ month extendable contractual role with a global pharmaceutical company in Waltham, MA. Must have minimum Masters degree and must have HPC high performance computing experience. REQUIREMENTS of the Cloud Infrastructure/AI/ML Engineer: • 3+ years of experience in cloud infrastructure, AI/ML development, and bioinformatics pipeline management • Advanced degree (MS or PhD) in Bioinformatics, Computational Biology, Computer Science or related field • Demonstrated expertise with various computing platforms (HPC, 7B, DNAnexus, AWS Sagemaker AI) • Strong background in NGS data analysis and pipeline automation • Cloud computing platforms (AWS, GCP) • Containerization technologies (Docker, Kubernetes) • Programming languages (Python, R, Bash) • Experience with NGS data analysis workflows and automation (Snakemake, Nextflow) • Experience developing/deploying AI/ML frameworks • Data visualization tools and libraries RESPONSIBILITIES of the Cloud Infrastructure/AI/ML Engineer: • Pipeline Execution & Management: Run and maintain bioinformatics pipelines on cloud platforms • Environment Management: Configure and support data/pipeline environments using 7B, and DNAnexus • AI Infrastructure: Set up and maintain environments for AI model development and inference (AWS Sagemaker AI) • Data Visualization: Create intuitive visualization tools for bench scientists and present data effectively • LLM Development: Develop RAG (Retrieval-Augmented Generation) LLMs for Gene Therapy GMU use cases • Automation: Develop and deploy agents to optimize/run routine NGS analyses and automate metadata verification Education: • Master’s (Required) Experience: • Cloud infrastructure: 3 years (Required) • AI/ML development: 3 years (Required) • bioinformatics pipeline management: 3 years (Required) • Python: 2 years (Required) • Bash: 1 year (Required) • R: 1 year (Required) • AWS: 3 years (Required) • GCP: 1 year (Required) • Docker: 1 year (Required) • HPC high performance computing: 3 years (Required)