ML Engineer(Databricks MLOps)

Anblicks Inc.; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A technology solutions provider in Hyderabad is seeking a seasoned Machine Learning Engineer to lead the design and operationalization of ML pipelines. The ideal candidate will possess significant experience in AI/ML architecture, with strong programming skills and a proven ability to collaborate across teams. Responsibilities include developing automated workflows and ensuring the performance of ML systems. This role demands expertise in modern technologies including Databricks and AWS, offering a dynamic work environment focused on innovative solutions.

Qualifications

• 8+ years of experience in enterprise architecture focused on AI/ML.
• 6+ years of professional experience in software development.
• Knowledge in modern programming languages such as Python or Java.

Responsibilities

• Develop and maintain enterprise architecture for AI/ML/GenAI.
• Design and deliver large-scale ML solutions.
• Build automated AI and ML workflows.

Skills

AI/ML experience

Software development

Problem solving

Data engineering

Education

Bachelor’s Degree in Computer Science

Tools

Python

Databricks

Apache Spark

AWS

TensorFlow

Job description

MLEngineer within theDataScience and Machine Learning teamleverages and third-party software to create solutions to business problems defined by specific business requirements. In this position, you will draw upon technical,AI/ML engineering, DataandMLOpsexperienceto solve complex marketing analytics problems on very large volumes of data.

As a Machine Learning (ML) EngineerYou will build and operationalize machine learning pipelines involving terabytes of data.You will have the responsibility to help define requirements, create software designs, implement code to these specifications, As an ML Engineer, you will be expected to:

Develop and maintain a comprehensive enterprise architecture for AI/ML/GenAI initiatives, ensuring alignment withoverall business strategy and technology roadmap.

Architect hyperscale MLOps solutionsand pipelines

Work with Applied Scientists, Data Scientists, Product owners, ML Engineers, and Software Engineers to design and deliver ML solutions in production at scale.

DevelopautomatedAI andML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML systems and data infrastructure.

Leverage AI to develop GenAI powered solutions to complement our data science and product buildcapabilities

Assess current state AI/ML/GenAI capabilities across various business domains, identify gaps, and design target state architectures to drive innovation, revenue growth and operational excellence.

Lead transformational initiatives to bridge the gap between current and desired AI/ML capabilities, collaborating with cross-functional teams to ensure successful implementation.

Establish governance frameworks and decision criteria for AI/ML and GenAI projects, ensuring adherence to industry standards, regulatory requirements, Responsible AI andarchitectural principles.

Create and maintain reference architectures, patterns, and best practices for AI/ML lifecycle and integration withinenterprise ecosystem.

Lead the technology evaluation and process improvements to drive Experimentation, Model Development and ML Ops at scale

Lead and drive standardization of LLM onboarding process, RAG pipelines and application development

Conduct architecture reviews and risk assessments for proposed AI/ML solutions, ensuring they meet security, scalability, and interoperability requirements.

Utilize advanced data science techniques (e.g., Natural Language Processing, clustering, predictive analytics, regression analyses, survival analysis, segmentation, and experimentation) to propose enhancements and innovations to business processes.

Conduct sophisticated statistical analyses and maintain high reliability of machine learning pipelines in production environments, ensuring minimal downtime and optimal performance.

Collaborate with business leadersand productto identify opportunities for AI/ML-driven innovation and guide the development of use cases that deliver tangible business value.

Foster a culture of continuous learning and innovation in AI/ML practices across the enterprise architecture team and broader organization.

BASIC QUALIFICATIONS

• 8+ ofyears ofexperience in enterprise architecture, with a focus on AI/ML integration and transformation projects.
• 6+ years professional experience in software development
• Bachelor’s Degree in Computer ScienceorAssociate Degree& 3+ years of development experience or equivalent experience
• Computer Science fundamentals in object-oriented design
• Computer Science fundamentals in data structures
• Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
• Knowledge of, at least, one modern programming language such asPython,Java, C++, C, Java,Pythonor Perl

PREFERRED QUALIFICATIONS

• 8+ years of experiencearchitectingscalable ML infrastructure and big data systems.
• Databricks Architect Certification is required
• 6+ years of architecting solutions using Databricks. Strong experience usingMosaic AI, Unity Catalogue,mlflow, workflow orchestration and otherdatabricksnative MLOps capabilities.
• At least1+ year experience inGenAI (Technical familiarity with 2 or more)-OpenAI API,Bedrock API,Vertex API,LangGraph,other agentic frameworks
• High attention to detail and proven ability to manage multiple, competing priorities simultaneously.
• Experience MLOps and orchestration tools such as Airflow, Kubeflow,DAGster,Optuna,Mlflowor other similar MLOps tools.
• Experience with operationalizing and migrating ML models into production at scale.
• Developing Large scale model inference solutions using parallel execution framework using spark, EMR, databricks
• Experience developing complex orchestration and MLOps pipelines stitching together large volumes of data for training and scoring
• Experience with Large Language Models, fine tuning and deployment frameworks using HuggingFace capabilities or cloud provider solutions such as Amazon Bedrock, Vertex AI model garden etc.
• Familiarity with Vector databases such as Pinecone, ChromaDB or similar tools.
• Experience in CI/CD/DevOps, Deployment and Automation Tool – CI/CD, Jenkins, Terraform, Cloud Formation Template or similar
• Proficiency with Apache Spark, EMR/DataProcandCloud based tools(Snowflake, Redshift, EMR, Glue, Step Functions, Lambda,Step functions, AWSBatch,or similaretc.).
• Experience with ML librarieslikeH20,scikit learnand deep learning frameworks (PyTorch, TensorFlow, etc.).
• Experience with end-to-end software development and life cycle of ML solutions.
• Excellence in technical communication with scientists and engineers.
• Atleast2yearsDatabase (SQL) experience,Linux
• At least6+ years ofAWS infrastructure experience-Cloud run,App server,RDS,S3,EC2, EMR or equivalent GCP experience

What will set you apart:

• Databricks Certification
• Knowledge of LLM observability platforms
• Good communication skills: communicate ideas clearly and effectively to other members of the analytics team and to the client at multiple levels (both technical and business)
• Analytic problem-solving skills with the ability to think outside-the-box
• Analytical thinker that excels at analyzing and understanding data to answer questions
• Excellent understanding of data concepts, data architecture, data manipulation/engineering, and data engineering design
• Passion for considering how projects fit into the wider business picture
• An understanding in multiple types of programming languagesin order tobe adaptable (statically typed vs. dynamically typed and object-oriented vs. procedural)
• Self-Starter – Able to work independently with little guidance
• Adaptable - Able to adapt to diverse technical challenges and systems
• Ability to formulate and present insights with gathered data to both technical and non-technical peers, leaders, and clients