Senior Machine Learning Engineer (Databricks)

Posted Yesterday
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3 Locations
Remote
Senior level
Artificial Intelligence • Information Technology • Professional Services • Analytics
The Role
Design, deploy, and optimize machine learning models and infrastructure using Databricks. Lead end-to-end model development, including data preparation, deployment, monitoring, and production scaling. Collaborate with data scientists, engineers, business stakeholders, and clients to deliver technical solutions. Mentor junior team members and apply advances in machine learning, NLP, computer vision, and MLOps to solve complex business problems.
Summary Generated by Built In

About Entrada AI

Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. We were recently named the Genie Partner of the Year (2026) for our work deploying Databricks Genie at enterprise scale—bridging the gap between AI ambition and the trusted, governed data required for accurate responses. With over 150 Databricks projects delivered, we unlock self-service analytics for Fortune 500 leaders.

Databricks invested in us because of our technical excellence, placing us in the "inner circle" of the ecosystem. For our engineers, this means direct access to product roadmaps, private previews, and the teams building the platform. You will join a team of industry veterans who value clean architecture over quick fixes. We don't just maintain pipelines; we solve complex architectural challenges.

About the Role

Entrada AI, Inc. is seeking an experienced Senior Machine Learning Engineer (Databricks) to join our growing team of consultants. In this role, you will be responsible for designing, developing, and deploying machine learning models and algorithms to solve complex business challenges with Databricks. You will work closely with data scientists, data engineers, and business stakeholders to build scalable and efficient machine learning solutions.

Key Responsibilities

  • Design and implement machine learning models and algorithms with Databricks, including predictive analytics, natural language processing, computer vision, and more.

  • Lead the end-to-end development process, from data collection and preprocessing to model deployment and monitoring.

  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

  • Optimize and fine-tune models for performance, accuracy, and scalability in a production environment.

  • Stay up-to-date with the latest advancements in machine learning and AI, and apply them to improve existing systems.

  • Mentor and guide junior engineers and data scientists in best practices for machine learning and data engineering.

  • Contribute to the development of machine learning infrastructure, including data pipelines, model serving frameworks, and monitoring tools.

  • Collaborate with client stakeholders to drive solutions to solve business problems.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field; PhD is a plus.

  • 5+ years of experience in machine learning engineering or related fields.

  • 3+ years of experience with Databricks

  • Proficiency in programming languages such as Python, R, or Java, with a strong understanding of machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

  • Experience with cloud platforms and MLOps tools, such as MLflow, for model deployment and monitoring.

  • Strong problem-solving skills and ability to work in a fast-paced environment.

  • Excellent communication and leadership skills, with the ability to work effectively across teams and influence stakeholders.

The Offer

Cooperation Models:

Poland: Available via Employment Contract (UoP) or B2B. 

Romania/ Greece: Available via B2B only. 

  • 100% Remote: Full flexibility to work from anywhere in Poland/ Romania / Greece

  • High-End Tech: Apple MacBook Air M4 15" provided to all engineers.

  • Referral Bonus: Bonus for bringing other top-tier engineers to the team.

  • Professional Growth:

    • Certification Support: Coverage for all Databricks technical certifications.

    • Industry Leadership: Support in reaching the highest tiers of Databricks expertise (such as the Champion program) tailored to your specific career track.

    • Personal Branding: Opportunities to present at global industry conferences and contribute to technical thought leadership.

    • Expert Mentorship: Direct collaboration with Databricks MVPs and core product teams, giving you a front-row seat to the platform's evolution.

Recruitment Process

  • Introductory Call (20 min): Short conversation with our Recruiter to discuss your background and expectations.

  • Technical Interview (60 min): Deep dive into your technical skills with our engineering team.

  • Optional Client Interview: Required only in specific cases.

  • Decision & Offer: We aim to close the process and provide feedback efficiently.

Skills Required

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field
  • PhD in a related field
  • 5+ years of experience in machine learning engineering or related fields
  • 3+ years of experience with Databricks
  • Proficiency in Python, R, or Java
  • Strong understanding of machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn
  • Experience with cloud platforms and MLOps tools such as MLflow for model deployment and monitoring
  • Strong problem-solving skills and ability to work in a fast-paced environment
  • Excellent communication and leadership skills, including the ability to work across teams and influence stakeholders
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The Company
60 Employees
Year Founded: 2023

What We Do

Entrada is a global Databricks-focused data and AI consulting and implementation partner. It helps organizations modernize data platforms and turn trusted data into business outcomes, offering data engineering, strategy and governance, migrations, AI/ML, analytics, concierge support, and training. Its teams work with clients from early data-platform migration through advanced use cases and production data products, tailoring solutions to industry needs and business results.

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