Databricks and AI Engineer

Job Title: Databricks + AI Engineer
Location: Remote
Experience: 4 10 Years
Employment Type: Full-time
About the Role
We are seeking a highly skilled Databricks + AI Engineer to design, build, and deploy scalable data and AI solutions on modern cloud platforms. The ideal candidate will have strong expertise in Databricks, machine learning, and distributed data processing, along with hands-on experience implementing AI/ML pipelines in production environments.

You will work closely with data engineers, data scientists, and business stakeholders to develop advanced analytics and AI-driven solutions that deliver measurable business value.
Key Responsibilities:
Design, develop, and optimize data pipelines using Databricks (Lakehouse platform).
Build and deploy scalable machine learning models using Apache Spark and ML frameworks.
Develop end-to-end ML workflows including data ingestion, feature engineering, model training, validation, and deployment.
Implement AI solutions leveraging NLP, computer vision, or generative AI techniques where applicable.
Work with cloud platforms such as AWS, Azure, or Google Cloud Platform to deploy AI solutions.
Optimize performance and cost-efficiency of large-scale distributed systems.
Implement CI/CD pipelines for ML models (MLOps best practices).
Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
Ensure data governance, quality, and security compliance.
Monitor model performance and manage lifecycle in production.
Required Skills & Qualifications
4+ years of experience in Data Engineering / Machine Learning.
Strong hands-on experience with Databricks (Delta Lake, Unity Catalog, Jobs, Workflows).
Expertise in Python and PySpark.
Experience with Apache Spark for distributed data processing.
Experience building ML models using frameworks such as:
TensorFlow / PyTorch / Scikit-learn
Experience with ML lifecycle tools (MLflow preferred).
Strong SQL skills and data modeling experience.
Hands-on experience with cloud platforms (Azure/AWS/Google Cloud Platform).
Understanding of MLOps, CI/CD, model deployment, and monitoring.
Knowledge of REST APIs and microservices architecture.
Preferred Qualifications
Experience with Generative AI / LLMs.
Experience integrating LLMs using frameworks such as LangChain.
Familiarity with vector databases.
Experience with real-time data processing (Kafka, streaming pipelines).
Databricks or cloud certifications.
Experience working in Agile environments.
Education
Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or related field.
Key Competencies
Strong problem-solving and analytical skills
Excellent communication and stakeholder management
Ability to work in a fast-paced, collaborative environment
Ownership mindset with focus on delivery

Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additional compensation may include benefits, discretionary bonuses, and equity.