<link id='css--app'rel="stylesheet" href="/dist/css/app.min.css"> Opportunities – Trilogy


MLOps Engineer at Comet.ml
New York City, NY, US

Comet is doing for Machine Learning what GitHub did for software. We allow data science teams to automagically track their datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility. Ever wondered how Linus felt when he invented GIT? How about the brains behind JIRA? Machine Learning teams operate like software teams 15 years ago and we started Comet.ml to write the rules of ML workflows and teams.

You’re welcome here

Working in a fast dynamic startup is challenging and lots of fun. We are looking for people who want to make an impact with their roles and decisions. If you are excited about pushing code that will change the way data scientists work all over the world, this is the right place for you. Comet.ml is backed by major VCs and we’re looking to expand our team. This role can be based in our NYC SoHo office or remote.

Comet.ml is an equal opportunity employer without regard to race, religion, color, sex, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship status, uniform service member status, marital status, pregnancy, age, medical condition, physical or mental disability, genetic information/characteristics and any other characteristic protected by State or Federal law.


As a MLOps Engineer  working out of our New York office or remotely, you will be the technical liaison with our prospective clients during the sales and customer success process . You will be responsible for delivering the technical win and product fit at customer accounts. It is critical for this role to build customer trust in our platform which will aid the sales and customer success organizations. You will lead the technical pre-sales relationship, propose technical architectures, demonstrate the product, anticipate concerns, and offer creative solutions to customer problems. You will also be responsible for providing feedback to product and engineering on key customer pain points and requirements that would inform the future roadmap.

The role requires someone who is both highly technical and a skilled relationship builder. You should be equally comfortable painting a vision of the technical possibilities of the platform with a C-level exec and whiteboarding workflows with customer’s data scientists and DevOps teams.

This role will be fully remote. Also, you will be working with a global team (large presence in Tel Aviv and Europe) – so some flexibility with work hours is required.


  • Partner with sales during the sales cycle and enable prospects to understand the benefits of leveraging the platform
  • Lead technical demonstrations onsite or via video conference
  • Work with the sales and customer success team to identify and qualify business opportunities and identify key customer technical objections. Develop the strategy to resolve technical impediments
  • Gather technical requirements from prospective clients and mapping the platform to the prospective clients’ unique requirements
  • (Potentially) travel on-site and aid customers in setting up the Comet platform
  • Create technical benchmarks
  • Partner with Marketing and Evangelism in the creation of blogs and technical content
  • Engage with the community on forums/groups


  • 1-8 years of experience as a sales engineer supporting a complex, technical product
  • Quick learner, self-starter and comfortable working with ambiguity
  • Deep and demonstrable knowledge of Python and ML frameworks such as Keras, PyTorch, Tensorflow
  • Good understanding of Linux
  • Previous experience with software development in Python
  • Background / Orientation with Machine Learning – a big plus
  • Bachelor’s degree in Mathematics, Engineering, Computer Science is helpful
  • Ability to understand the workflow and tools used by data scientists
  • Excellent communicator and presenter; able to win the confidence of a technical audience and simplify messaging
  • A deep understanding of data scientists’ needs and pain points is a big plus