Lead Consultant, Machine Learning Engineer

Sorry, this job was removed at 04:10 p.m. (CST) on Friday, Jul 18, 2025
Arlington, VA
In-Office
Big Data • Professional Services • Business Intelligence • Consulting
The Role

Lovelytics is seeking a Machine Learning Engineer (Lead Consultant) with experience delivering strategic Databricks client engagements to join our ML Practice.

This Lead Consultant will play a key role in delivering on client engagements related to  ML Pipelines, NLP, data integrations, and data modeling. Our ideal candidate will have strong consulting experience, technical proficiency in Machine Learning, and the ability to manage client relationships effectively. In addition to the technical capabilities for this role, we are looking for someone who wants to work in a collaborative, dynamic, and inclusive environment and has a passion for bringing meaning to data.

 This role is open to remote candidates in the the US as well as Ontario, Canada
This role is not open for work sponsorship at this time.

Primary Responsibilities:

  • Utilize consulting and technical skills to be able to work in a client-facing project environment independently.
  • Be responsible for your own execution and sometimes lead individual work streams on client engagements as assigned and under supervision of engagement lead.
  • Collaborate with other team members to successfully deliver on projects.
  • Work effectively and directly communicate with both internal and client and/or partner teams.
  • Develop full ownership of your execution on client engagements, you'll become involved in the project planning and solution stages of engagements as well.
  • Hands on ML engineering tailored to client needs, including MLOps, Pipelines, NLP, text generation, and image synthesis.
  • Deploy production-level machine learning pipelines to impact the business of our clients
  • Contribute to real-time data processing solutions and managed streaming data.
  • Implement security and compliance measures for data pipelines.
  • Design and implement version control and branching strategies and integrate them into CI/CD for promoting and testing in higher environments.
  • Work with engagement leads and directors to gain exposure in the design and architecture of solutions

Our Ideal Candidate's Skills and Experiences:

  • B.S. in Computer Science or equivalent
  • 3-5 years' experience in Machine Learning and big data. At least 2 years working directly with clients and/or external stakeholders.
  • Ability to work with popular NLP frameworks such as Spark NLP or Hugging Face Transformers in pytorch, tensor flow etc.
  • Extensive knowledge of data warehousing concepts and hands-on experience deploying pipelines using Databricks 
  • Data modeling and database design skills and knowledge of version control
  • Excellent verbal and written communication skills
  • Understands and utilizes Lovelytics tools and client tools 

What We Promise You:

  • Exciting projects with great clients in varying departments and verticals across the world
  • The ability to work closely with experienced data engineers and quickly grow and expand your skillset
  • The ability to work closely with all sizes of companies, ranging from Fortune 100 to small local businesses
  • A workplace where you are encouraged to challenge the status quo and develop new technologies, methodologies, and processes
  • A diverse team consisting of data gurus, experience seekers, and entrepreneurial minds that are always pushing to be better

Lovelytics is an Equal Opportunity Employer. This means you don’t have to worry about whether your application process will be fair. We consider all applicants without regard to race, color, religion, age, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, veteran status, or disability. 

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The Company
HQ: Arlington, VA
70 Employees
Year Founded: 2017

What We Do

Lovelytics is a data and analytics consultancy. We partner with people, teams, and organizations to deliver services and build solutions that drive outcomes while promoting self-sufficiency through hands-on enablement.

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