Computomic was founded in 2019 with a vision to design and deploy mission critical and highly differentiated Data & AI solutions for companies looking to migrate their data stack from legacy data platforms such as Teradata, Cloudera, Datastage and Informatica to modern data platforms like Databricks. Over the last few years, we have become a leading Databricks partner, building a strong and mature Databricks practice and delivering Databricks migration projects for some of the world’s leading companies.
Our consulting services and tooling help companies realize value from their data by modernizing their data stack to the latest data platform technologies like Databricks. We use accelerators that save companies up to 80% of time and money moving data from legacy platforms to Databricks. We help customers find margins of improvement in everything they do, which when aggregated creates a transformative effect on their business.
We are a nimble and rapidly growing company with a global footprint, and a focus on Data & AI. We have built an impressive depth of Data & AI experts and experts in BI/ Dashboarding tools such as PowerBI and Tableau
Our name Computomic is derived from two words: Computers and Atomic. We believe in making one small change (Atomic) at a time, so that the cumulative effect of all the changes delivers a massive impact.
The Role
We are one of the fastest growing partners for Databricks and are looking for a Machine Learning Engineer to help us build out one of the most impactful GenAI practices in the industry!
You will have the opportunity to shape the future of the GenAI landscape at leading Fortune 500 companies and cutting-edge startups. You will work on the industry’s most challenging customer engagements to solve big data problems using leading cloud platforms such as AWS/Azure/GCP and Databricks.
You will have the opportunity to work with some of the leading experts in the data and AI industry and develop a deep understanding of Databricks and adjacent technologies. You will be empowered to architect, scope, negotiate and lead data GenAI projects, develop best practices and thought leadership, and represent both Computomic and Databricks at Industry forums and events.
You will join a team of experts with the autonomy and flexibility to make quick decisions, forge your own paths and adapt to the changing market and customers’ needs.
The impact you will have:
- Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation
- Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains
- Advise data teams on various data science such as architecture, tooling, and best practices
- Present at conferences such as Data+AI Summit
- Provide technical mentorship to the larger ML SME community in Databricks
- Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap
What we look for:
- Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
- 4+ years of hands-on industry ML engineering experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP
- Graduate degree in a Computer Science/Engineering or equivalent practical experience
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
- Passion for collaboration, life-long learning, and driving business value through ML
- [Preferred] Experience working with Apache Spark to process large-scale distributed datasets
What we offer:
- Excellent Compensation, including bonuses
- 401k Plan and Employer matching
- Robust Health and Wellness Benefits – including employer paid health insurance for employees
- Referral Program
- Paid Time Off and Sick Leave
- Professional Development Assistance
- Excellent work culture
- Remote/Hybrid working option (location is Princeton, NJ)
- Training & Certification Plan, on Databricks + adjacent technologies
- Career Development Plan, including management/ leadership training
Are you passionate about this opportunity, but speculating that you don’t meet 100% of the experience we’re looking for? We still want to hear from you!