AI Engineer - MLOps

Company Overview :

V4C.ai is a leading innovator in data and AI, dedicated to helping enterprises modernize their data platforms and accelerate AI initiatives. With proven expertise in Databricks, we transform complex data challenges into scalable outcomes, from Lakehouse implementation and workflow migration to advanced ML pipelines.

We provide comprehensive solutions across various industries, including Financial Services, Retail & Consumer Goods, Manufacturing, and Healthcare & Life Sciences, driving innovation, efficiency, and significant business impact. Our team is committed to delivering cutting-edge solutions in Generative AI, Machine Learning, MLOps, and Data Governance, empowering businesses to leverage their data for strategic advantage.

Role Overview :

As an AI Engineer at V4C.ai, you will play a pivotal role in designing, developing, and deploying advanced AI and machine learning solutions that drive significant business impact for our clients.

You will work on complex data challenges, transforming raw data into actionable insights and robust AI applications.

This role demands a strong technical background in machine learning engineering, MLOps, and proficiency with leading data platforms like Databricks, contributing to our mission of accelerating AI adoption and innovation for enterprises.

Key Responsibilities :

- Design, develop, and implement scalable machine learning models and AI-driven solutions using Python and relevant libraries.

- Build and optimize MLOps pipelines for model deployment, monitoring, and retraining in production environments.

- Collaborate with data scientists and clients to translate business requirements into technical specifications for AI projects.

- Integrate AI/ML solutions with existing data platforms, particularly Databricks, ensuring seamless data flow and performance.

- Perform data preprocessing, feature engineering, and data analysis to prepare datasets for model training.

- Contribute to the architectural design of robust, high-performance, and cost-effective AI systems.

- Troubleshoot and optimize existing machine learning models and pipelines for improved accuracy and efficiency.

- Stay abreast of the latest advancements in AI, machine learning, and data engineering to continuously improve our offerings.

- Participate in code reviews, ensuring adherence to best practices and high-quality standards.

- Document technical designs, processes, and operational procedures for developed AI solutions.

Required Qualifications :

- Experience : 5 - 10 years of professional experience in AI/ML engineering, data science, or a related field.

- Programming : Strong proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

- Platforms : Proven experience with Databricks platform, including Databricks SQL, MLflow, and Delta Lake.

- MLOps : Solid understanding of MLOps principles and practices for deploying and managing ML models in production.

- Cloud : Experience with cloud platforms (AWS, Azure, or GCP) for deploying and managing AI/ML workloads.

- Fundamentals : Strong foundation in data structures, algorithms, and object-oriented programming.

- Soft Skills : Excellent problem-solving skills and the ability to work independently or as part of a collaborative team.

- Education : Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.

Preferred Qualifications :

- Experience with Dataiku or similar data science and machine learning platforms.

- Hands-on experience with Generative AI models and large language models (LLMs).

- Familiarity with containerization technologies such as Docker and Kubernetes.

- Experience with data governance and ensuring data quality for AI initiatives.

- Knowledge of big data technologies beyond Databricks (e.g., Spark).

- Certifications in Databricks or relevant cloud platforms.

Tech Stack / Tools :

- Programming Languages : Python, SQL

- Data Platforms : Databricks (Lakehouse, SQL, MLflow, Delta Lake), Dataiku

- Machine Learning Frameworks : TensorFlow, PyTorch, Scikit-learn

- Cloud Platforms : AWS, Azure, GCP

- MLOps Tools : MLflow, Databricks Workflows, Docker, Kubernetes

- Version Control : Git

Compensation & Benefits :

- Annual Salary : INR 25 - 30 LPA

- Comprehensive health and wellness benefits.

- Opportunities for professional development and continuous learning.

- A dynamic and supportive work environment.

- Additional benefits like paid time off, retirement plans, etc. will be discussed during the interview process.

Skills

Python, Machine Learning, MLOps, Artificial Intelligence, Databricks, AI Integration, Data Analytics, SQL, Cloud, Tensorflow