TalentBurst
Job Title: ML Engineer
Location: Waltham, MA 02451
Duration: 12 Months
Only W2 Accepted
Description Position Overview We are seeking an experienced Cloud Infrastructure/ AI/ML/ Data Engineer to support variety of projects across Genomic Medicine Unit (GMU) research and platform work. This contractor role focuses on providing infrastructure solutions to enable AI/ML models developments and applications. As such, the position will require pipelines execution, environment management, AI/ML model development/deployment, management of data for various bioinformatics workflows. This position is 1 year contract with possibility of extension. Full time, on site at Waltham, MA.
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
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Description Position Overview We are seeking an experienced Cloud Infrastructure/ AI/ML/ Data Engineer to support variety of projects across Genomic Medicine Unit (GMU) research and platform work. This contractor role focuses on providing infrastructure solutions to enable AI/ML models developments and applications. As such, the position will require pipelines execution, environment management, AI/ML model development/deployment, management of data for various bioinformatics workflows. This position is 1 year contract with possibility of extension. Full time, on site at Waltham, MA.
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
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