ML Ops Specialist

at  Slingshot Aerospace

REQUIREMENTS

• 2+ years in ML Operations, FMOps, data science deployment, or relevant experience which may include demonstrated experience designing and implementing databases, data systems, feature stores, and modeling pipelines in a data science team environment.
• Bachelor’s degree in computer science, engineering, mathematics, data science, physics, or other related disciplines.
• Proficiency in a formal programming language (e.g. Julia, Python, java/kotlin, C/C++).
• Ability to identify creative data and feature solutions for challenging projects.
• Experience working with teams and groups of data scientists, engineers, or computer scientists.
• Demonstrated ability to develop and deploy a host of data and data science services in the AWS cloud using Terraform or similar.
• Familiarity with software development lifecycle and CI/CD processes
• Ability to work within multi-disciplinary teams in a fast-paced, evolving operational environment that spans military, government, and industry partners.
• Excellent verbal and written communications skills.
• Experience with distributed computing frameworks such as Ray, Spark, or Dask
• Previous experience with machine learning, AI, and data science processes.

PREFERRED SKILLS

• Experience with aerospace and astrodynamics datasets.
• Interest in working at a startup organization with a broad set of opportunities and challenges.
• History with, and understanding of data science approaches and opportunities.
• Experience developing, implementing, and transitioning sophisticated technology to production.
• These skills are guidelines, not hard and fast rules. You don’t have to meet every qualification listed- if your skills are transferable and you meet the minimum requirements, we encourage you to apply.
  Location: Remote, United States
  Pay Range: $95,000-$145,000

WHAT YOU’LL DO

As the MLOps Science Engineer you will directly impact Slingshot’s vision; to accelerate space sustainability to create a safer and more connected world. In your new role you will design, develop, and implement feature architectures, data systems, and processes to facilitate team effectiveness and improve data science products.

POSITION RESPONSIBILITIES

• Collaborate with the MLOps Lead and data scientists to identify systems and processes likely to deliver effective features to modeling pipelines
• Build the infrastructure upon which the Science team develops and deploys models.
• Work with members of the Science team to identify how to deliver models into our production infrastructure.
• Implementing ETL processes for a broad range of data types.
• Participate in a strong matrixed science team and culture and work directly with engineering partners to facilitate the flow, integrity, and utility of data science products.
• Execute all position responsibilities in alignment with Slingshot’s core values, mission, and purpose