Machine Learning Engineer

Posted 7 Hours Ago
Easy Apply
Be an Early Applicant
3 Locations
Remote
Hybrid
Mid level
AdTech • Big Data • Information Technology • Marketing Tech • Sales • Software
Bombora helps sales and marketing teams focus on businesses that are actively interested in what they sell.
The Role
As a Machine Learning Engineer at Bombora, you will develop and deploy ML and NLP solutions, create production-grade pipelines using GCP and Python, and collaborate with teams to enhance model performance. Responsibilities include workflow implementation, model monitoring, and working with APIs.
Summary Generated by Built In

The true B2B data pioneer, Bombora connects the B2B ecosystem in a one-of-a kind Data Cooperative—enabling a holistic view of an account’s research and consumption behavior. From this data, Bombora derives actionable insights that make it possible for brands, agencies, and publishers to identify, understand, and reach their prospects and customers, throughout the buyer and user experience, across the activation platforms of choice.

Bombora is continually recognized by analyst firms as a leader in Intent data powering GTM data solutions.

As our Machine Learning Engineer, you will play a key role in building and deploying cutting-edge ML and NLP solutions that drive real business impact. You will work on high-scale, production-grade ML pipelines using GCP, Python, and SQL, collaborating closely with data scientists, engineers, and product leaders to bring models from research to deployment. This role offers a unique opportunity to work on complex deep learning challenges, optimize models for real-world performance, and contribute to a growing, high-impact ML ecosystem.

We thrive on innovation, collaboration, and end-to-end ownership—every engineer has the autonomy to experiment, build, and deploy solutions that shape key business decisions. If you’re looking for a fast-paced, highly technical, and impact-driven environment, this is the perfect place to grow your ML expertise and make a tangible difference

You will…

  • Implement end-to-end ML workflows on GCP (preferred), integrating data pipelines and model deployment.
  • Work with SQL / PL SQL to clean, transform, and prepare large datasets for ML models.
  • Write efficient Python code, optimize model inference, and develop APIs for model integration.
  • Apply statistical methods to evaluate and improve model performance.
  • Work closely with data engineers, software teams, and product managers to bring ML solutions into production.
  • Implement model monitoring, retraining pipelines, and troubleshooting workflows to keep models accurate over time
  • Tune hyperparameters, optimize inference speed, and ensure models are cost-effective at scale

 You have…

  • 4+ years experience in developing ML applications and ML models on Cloud (GCP preferred) 
  • Proficiency in Python for ML model development, data manipulation, and automation.
  • Hands-on experience with frameworks like TensorFlow, PyTorch, or Hugging Face.
  • Ability to build and integrate ML models with APIs (e.g., Flask, FastAPI, or cloud-based endpoints).
  • Solid understanding of probability, hypothesis testing, and model evaluation techniques.
  • Prior experience shipping ML models into production at scale
  • Familiarity with Git, Docker, and ML CI/CD pipelines for automated testing and deployment
  • Ability to design ML systems that handle high-throughput, real-time, or batch processing workloads efficiently

Bonus points for...

  • Experience with CI/CD for ML models, model monitoring, and orchestration tools like Kubeflow or Airflow
  • Knowledge of distributed computing frameworks (e.g., Spark, Dask) for large-scale ML processing.
  • Understanding of LLMs and vector search for enhancing NLP applications

Perks and Benefits

  • Health / Dental / Vision
  • Flexible Spending / Health Spending Accounts
  • Flexible Vacation / Paid Holidays / Summer Fridays
  • Education / Tuition Assistance / Annual Learning Stipend
  • 401K / Match
  • Generous Parental Leave (16 weeks primary/12 secondary)
  • Commuter Benefits
  • On Demand Learning (Udemy)
  • Team Lunches / Outings / Events (Yes! We found a way to do virtually!)

Compensation Package

  • The salary range for this position is $155,000 to $170,000.  Actual compensation may vary and will be based on a candidate’s qualifications, skills, experience, and location.
  • Equity

At Bombora, we embrace diversity because it breeds innovation. Bombora is an equal-opportunity employer and participates in E-Verify. Employment offers are contingent upon completion of successful background checks.

Top Skills

Python

What the Team is Saying

Charles
Kyle
Brian Ly
Havona
Jen
Sherry
The Company
HQ: New York, NY
152 Employees
Hybrid Workplace
Year Founded: 2014

What We Do

Bombora’s mission is to revolutionize the martech industry through the use of data built on an ecosystem of quality, collaboration, and innovation. Our data is high quality, publisher sourced, accurate, flexible, and backed by the expert team that invented Intent data. From cutting out the waste and easing the frustration of traditional marketing methods, to the way we give our Bommies the support to grow into their best selves – we believe in sustainability, and that belief informs all that we do.

We’re not just the leader in B2B Intent data. We invented it.



Why Work With Us

At Bombora, we put people first. Better yet, we encourage employees to not just work here, but to grow here. Bommies are empowered to contribute from spaces and places that best serve the needs of the customer, organization, and themselves. This philosophy is proven through our company values and reflected in our policies and company culture.

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Bombora Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Our hybrid policy offers employees an office for when they want one. We have offices in New York and Reno, Nevada. Bombora also hosts annual Company-wide kickoffs in January, so employees get a chance to fly into our NY office to meet fellow Bommies.

Typical time on-site: Flexible
HQNew York, NY
Reno, NV
Learn more

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