Machine Learning Solutions Engineer

Machine Learning Solutions Engineer, EMEA

As we look to expand our EMEA presence, we're hiring Machine Learning Solutions Engineers and considering candidates at the Senior to Principal-level. Special consideration will be given to candidates based in the U.K., based on current expansion plans.

Who We Are

At Gretel, our mission is to build the world’s first developer platform for synthetic data. Our platform solves the data bottleneck problem for developers, data scientists, and AI/ML researchers across multiple modalities including tabular, time-series, relational, language and image. Gretel's APIs automatically fine-tune AI models to generate synthetic data on-demand while protecting privacy and maintaining the utility and accuracy of the original data. Designed by developers for developers, our APIs make it simple to generate anonymized and safe synthetic data so you can preserve privacy and innovate faster.  

We’re a highly collaborative remote-first company with employees across the US & Canada (and now, EMEA). Our innovative and transparent culture offers employees the autonomy, tools, and trust to act like owners. We’re disrupting how organizations innovate with data and are looking for talented Machine Learning Solutions Engineers to join our mission! 

The Impact You’ll Have

As a Machine Learning Solutions Engineer, you'll articulate Gretel’s mission and value to new prospects and existing customers, working side-by-side with our sales, engineering, product, and applied science teams. You will play a critical role in driving the success of our GTM efforts by helping to differentiate the platform throughout the sales process, drive value-centered proof of concepts (POC) and paid pilots, and help existing customers better utilize synthetic data via repeatable, scalable use cases. You will echo and amplify our data science thought leadership by guiding meaningful and valuable customer experimentation with the platform.


  • Build custom prototypes and product demos that highlight end-to-end operationalized use cases of Gretel. These may be both for pre and post sales objectives.
  • Be the voice of the customer, communicating back experimental results and empirical experience gained from the field and critical for our internal applied science research.
  • Be the voice of the customer by also proactively identifying opportunities in our product based on trends identified across customer needs, and build solutions to address these emerging patterns.
  • Conduct and guide research in the field, working with our most pioneering customers to advance what is possible with our platform.
  • Augment the technical discovery during the sales lifecycle to deeply understand prospects’ ML and engineering requirements
  • Help the account teams differentiate proposed approaches versus open source and competitive solutions.
  • Stay up-to-date with industry trends, best practices, and advancements in generative AI, data privacy, and cloud infrastructure. 


  • 5+ years of experience in a technical customer-facing role serving Enterprise customers and showcasing a track record of successful technical sales support. Ideally this will include value based selling of a hybrid solution.
  • Fluency in Python, utilizing Collab or Jupyter notebooks, and working with open-source libraries.
  • Deep experience working with data pipelines and orchestration / tooling for the modern data stack.
  • Previous hands on engineering experience in Data Engineering and MLOps. 
  • Exceptional presentation and communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
  • Ability to operate with high horsepower, adept at frequent context switching and working on multiple projects at once with expansive ownership and prioritization.
  • Capable of owning problems end-to-end, a deep curiosity to acquire knowledge, and the humility to figure out what is missing to get the job done.
  • Passion for thriving in a dynamic and ambiguous environment.
  • Willingness to travel occasionally (up to 20%) for customer meetings, conferences, and industry events as needed. 
  • Fluency in English is required; proficiency in additional languages spoken in the EMEA region is a plus.

Nice To Haves

  • 3+ Years of experience working with state-of-the-art machine learning and deep learning models.
  • 3+ Years of exposure to modern machine learning frameworks and technologies.
  • Experience with Kubernetes, containers, and CI/CD.
  • Knowledge of data privacy concepts, data security, and data privacy regulations including anonymization, de-identification, privacy by design, GDPR, etc.
  • Experience implementing or working with data anonymization or data obfuscation techniques is preferred.
  • Experience working at a growth-stage startup where you were involved in the process buildout and scalability.

We think the best ideas come from the blending of diverse perspectives and experiences, which will lead to a stronger company and advancements in technologies.  We hire individuals whose peers call them subject matter experts, whose curiosity draws them to new edges of their field and who like to laugh.  We are deeply collaborative, apolitical and mission-oriented.

Gretel is an equal opportunity employer. Individuals seeking employment and employees at Gretel are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. 

Accommodations: We celebrate diversity and are committed to creating an inclusive environment for all candidates and employees. If you need assistance or an accommodation due to a disability, please let your recruiter know.

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