Machine Learning Engineer

Introduction to Demandbase: 

Demandbase is the Smarter GTM™ company for B2B brands. We help marketing and sales teams overcome the disruptive data and technology fragmentation that inhibits insight and forces them to spam their prospects. We do this by injecting Account Intelligence into every step of the buyer journey, wherever our clients interact with customers, and by helping them orchestrate every action across systems and channels - through advertising, account-based experience, and sales motions. The result? You spot opportunities earlier, engage with them more intelligently, and close deals faster. 

As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have offices in the San Francisco Bay Area, Seattle, and teams in the UK and India, and allow employees to work remotely. We have also been continuously recognized as one of the best places to work in the San Francisco Bay Area.

We're committed to attracting, developing, retaining, and promoting a diverse workforce. By ensuring that every Demandbase employee is able to bring a diversity of talents to work, we're increasingly capable of living out our mission to transform how B2B goes to market. We encourage people from historically underrepresented backgrounds and all walks of life to apply. Come grow with us at Demandbase!

About the Role
Demandbase is seeking a Machine Learning Engineer to join our Central Data Science team, where you’ll play a key role in building and deploying scalable machine learning solutions that transform the B2B buyer’s journey. You’ll work at the intersection of data science and engineering, developing and operationalizing machine learning models that enhance product offerings across account ranking, intent detection, and ad optimization.

As a Machine Learning Engineer, you will collaborate closely with data scientists, product managers, and engineers to productize ML algorithms, optimize model performance, and ensure smooth deployment at scale. A strong proficiency in Scala is preferred, as many of our systems are built with Scala to support high-volume data processing.

The compensation range for this role is: $160,000 - $218,000

What you'll be doing:

• Model Deployment and Optimization: Develop and deploy machine learning models that drive real-time business insights and impact campaign KPIs.
• Pipeline Development: Build robust data pipelines to support ML model training, testing, and deployment at scale, leveraging Python and Scala as core technologies.
• Cross-functional Engineering Collaboration: Work closely with data engineering, product management, and UX design teams to ensure models integrate seamlessly into our platform.
• Performance Monitoring and Tuning: Implement monitoring systems to evaluate model performance in production and develop strategies to optimize and retrain models as needed.
• Drive ML Innovation: Stay updated on industry advancements and integrate new techniques to maintain cutting-edge capabilities.

Project Highlights

• Account Intelligence: Design systems to map billions of IPs and cookies to companies for improved account ranking and personalization.
• Real-Time Intent Signals: Engineer models to trigger alerts based on real-time intent signals, enabling sales teams to act on high-value leads.
• Ad Optimization: Optimize ad performance with real-time bidding, click-through rate, and engagement models using reinforcement learning algorithms.

What we're looking for:

• Experience: 5+ years in machine learning engineering or a related field, with hands-on experience in deploying production-level models.
• Education: Degree in Computer Science, Machine Learning, Engineering, or related fields (e.g., Mathematics, Statistics, Physics).
• ML Engineering Proficiency: Demonstrated expertise in deploying and optimizing machine learning models in one or more areas:
  • Ranking & Recommendation Systems
  • Ad Optimization, Real-Time Bidding
  • Reinforcement Learning
  • Experimentation (A/B Testing)
• Technical Skills:
  • Proficient in Python and ML libraries (Scikit-Learn, Pandas, Numpy, etc.)
  • Experience with Scala (preferred) for data pipeline and production optimization
  • Familiarity with ML frameworks like TensorFlow, Keras, PyTorch, and SparkML
  • Strong SQL and No-SQL database skills
• Cloud & Data Engineering Tools: Google Cloud Platform or AWS experience preferred, along with Spark and BQML.

Benefits:

Our benefits include options for up to 100% paid Medical and Vision premiums for employees, flexible PTO policy, no internal meeting Fridays, Modern Health mental wellness platform, and 11 paid holidays and 2 additional weeks where all Demandbase employees take off (the week of July 4th and the week of Thanksgiving). Plus 401(k), short-term/long-term disability, life insurance, and all those good things.

Our Commitment to Diversity, Equity, and Inclusion at Demandbase

At Demandbase, we believe in creating a workplace culture that values and celebrates diversity in all its forms. We recognize that everyone brings unique experiences, perspectives, and identities to the table, and we are committed to building a community where everyone feels valued, respected, and supported. Discrimination of any kind is not tolerated, and we strive to ensure that every individual has an equal opportunity to succeed and grow, regardless of their gender identity, sexual orientation, disability, race, ethnicity, background, marital status, genetic information, education level, veteran status, national origin, or any other protected status. We do not automatically disqualify applicants with criminal records and will consider each applicant on a case-by-case basis.

We recognize that not all candidates will have every skill or qualification listed in this job description. If you feel you have the level of experience to be successful in the role, we encourage you to apply!

We acknowledge that true diversity and inclusion require ongoing effort, and we are committed to doing the work required to make our workplace a safe and equitable space for all. Join us in building a community where we can learn from each other, celebrate our differences, and work together.

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