[Hiring] AI/ML Engineer @Dysrupit

Role Description

We are seeking an AI/ML Engineer to deliver production-grade AI/ML solutions on Databricks for enterprise clients. You will build robust pipelines, productionize machine learning and Generative AI use cases, and help clients move from notebook experimentation to reliable, governed, at-scale production systems. You will work closely with data scientists, ML scientists, and solution architects, translating client requirements into reliable, governed, and scalable solutions. This role is the right fit if you love hands-on AI/ML engineering, enjoy direct client collaboration in a consulting environment, and stay current with the latest in Databricks tooling, MLOps, and GenAI.

Qualifications

• 3+ years of experience as an ML Engineer or in a similar role, with meaningful hands-on time on the Databricks platform.
• Strong Python and PySpark skills, with the ability to write production-quality Spark jobs, not just notebooks.
• Practical experience delivering production Generative AI or agentic systems, including RAG architectures, LLM orchestration frameworks (e.g., LangChain, LangGraph), and AgentOps tooling (evaluation, monitoring, governance).
• Extensive hands-on industry data science and ML experience using common tools such as pandas, scikit-learn, and PyTorch.
• Background supporting large-scale consumer or enterprise ML systems (recommenders, ranking, forecasting, personalisation).
• Experience with MLflow or a comparable tool for experiment tracking, model registry, and model serving.
• Solid SQL skills and experience with cloud data platforms (Azure, AWS, or GCP); Azure Databricks experience is a plus.
• Comfortable working directly with clients or cross-functional stakeholders to scope and deliver technical work.

Requirements

• Build and productionize feature pipelines and training/serving pipelines for ML and GenAI use cases, using MLflow for experiment tracking and model management.
• Support the delivery of Generative AI and agentic systems on Databricks, including data preparation for RAG pipelines, vector search integration, and AI/BI tooling such as Databricks Genie Spaces.
• Help stand up new AI use cases end to end on Databricks, from data preparation through to a working prototype, working alongside data scientists to move ideas from notebook to production.
• Build reusable Databricks templates and accelerators for common AI/ML use cases (RAG, agentic assistants, forecasting, personalisation), reducing time-to-development for new client engagements.
• Optimize Databricks jobs, clusters, and workflows for cost, performance, and reliability at production scale.
• Work directly with client engineering teams and stakeholders to gather requirements, troubleshoot issues, and hand over documentation and runbooks.

Preferred Experience

• Practical experience with Delta Lake and lakehouse/medallion architecture patterns.
• Working knowledge of Unity Catalog or equivalent data governance and access-control tooling.
• Prior consulting or professional services experience in AI/ML delivery.
• Familiarity with experimentation and A/B testing pipelines built on Databricks.
• Exposure to causal inference or applied statistics (e.g., uplift modelling, Double ML) to support AI use case development.

Certifications Preferred

• Databricks Certified Machine Learning Associate or Professional
• Databricks Certified Generative AI Engineer Associate

Benefits

• Competitive compensation package commensurate with experience
• Government-mandated benefits plus supplemental Health Insurance
• Collaborative and professional work environment
• Career growth opportunities within a growing organization
• Remote work arrangement