Database Developer III | Cloud Infrastructure | AI | ML Engineer
Integrated Resources - Waltham, Massachusetts, United States, 02254
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Overview
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Overview
Database Developer III | Cloud Infrastructure | AI | ML Engineer Location:
Waltham, MA 02451 - Hybrid Duration:
12 Months+ (Possible Extension)
Pay range:
$75 - $80/hr. on W2
Must Have Experience:
Minimum 3 years of experience in cloud infrastructure, AI/ML development, and bioinformatics pipeline management. MS or PhD Degree. Demonstrated expertise with various computing platforms (HPC high performance computing, AWS, 7B, DNAnexus, AWS Sagemaker AI). Cloud computing platforms (AWS, GCP) -
Must have
requirement: AWS or similar. Python and Bash (must have). Strong communication skills. Experience developing/deploying AI/ML frameworks.
Nice to Have / Preferred Experience:
Containerization technologies (Docker, Kubernetes). S3 AWS Storage, data storage. Experience with NGS data analysis workflows and automation (Snakemake, Nextflow).
Position Overview: We are seeking an experienced Cloud Infrastructure / AI/ML / Data Engineer to support a variety of projects across the Genomic Medicine Unit (GMU) research and platform work. This contractor role focuses on providing infrastructure solutions to enable AI/ML models development and applications. As such, the position will require pipelines execution, environment management, AI/ML model development/deployment, and management of data for various bioinformatics workflows.
Required Experience:
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.
Key Responsibilities:
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.
Technical Skills:
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.