Company Description

Our focus is to help Biotech/BioPharma, MedTech, Digital Health, Healthcare, Insurance, and Tech organizations accelerate innovation, enable data-driven decisions, and create AI/ML applications. We leverage AI to solve today’s hardest challenges. We are driven to make the world a better place by providing consulting services and building applications to improve outcomes and help our clients stay ahead of the competition.

Our team is composed of creative and results-focused individuals who excel at solving real-world problems. Our diverse backgrounds bring technology and expertise from various disciplines including neuroscience, physics, engineering, computational biology, genomics, mathematics, and computer science. 

Our culture is vibrant, connected, rooted in our core values statement that:
Our work matters. Our clients are partners. Our work is our reputation. We own our choices. We are always learning. We support and challenge each other.

This role is eligible for flexible hours and remote work.

Job Description

This role is ideal for a results-focused individual interested in developing solutions that support and augment data science initiatives across healthcare and life science companies using a wide variety of tools and technologies.

MDS Software Engineers collaborate with Data Scientists to build and deploy internal products and client solutions across multiple domains and projects. Our team is pragmatic, curious, and works to consistently build clean, concise solutions.

Qualifications

• 1+ years of experience deploying scalable applications onto cloud infrastructure (GCP, AWS, Azure)
• 1+ years of experience with software development in one or more programming languages (Python, C++, Java, JavaScript, etc)

We generally require applicants to have 1+ years of prior engineering experience on data-intensive projects to qualify for this role.

Additional Information

Nice to have

• Project/product management skills/experience
• Experience with productionized AI/ML systems deployed onto cloud infrastructure
• Experience building and maintaining data ingestion pipelines at scale
• Cloud certifications for GCP or AWS (e.g. AWS Associate Architect)
• Experience deploying containers and orchestrating them at scale (Docker, Kubernetes) in a cloud environment
• Exposure to biological/clinical data (omics, imaging, biosensors, etc.)
• Exposure to data storage and access patterns
• Experience with containerization and orchestration tools (Docker, Kubernetes, Argo Workflows)

Tools We Love

• Programming Languages: Python, Javascript
• DevOps: Git, Jenkins
• Containerization and Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform, Helm
• Workflow Tooling: Kubeflow, MLFlow, DVC, Argo Workflows
• Data Processing: dbt, Pandas, Scikit-Learn, AWS Glue, Spark, Dask, Prefect, Airflow
• Data Stores / Databases: Redshift, Snowflake, BigQuery, Cloud SQL, DynamoDB, S3 and many others

Skill Levels

• Engineer - 1-3 years experience/relative skills
• Senior Engineer - 2-4 years experience/relative skills
• Lead Engineer - At least 3 years experience/relative skills
• Principal Engineer - At least 5 years experience/relative skills