AI-ML Data Engineer

CoreFlex Solutions Inc.; Pune District; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A leading technology company in Pune is looking for a Data Engineer with expertise in AI and Machine Learning. The successful candidate will design and maintain data pipelines, develop machine learning models, and collaborate with cross-functional teams. Requirements include proficiency in Python, SQL, and data manipulation libraries, along with a Bachelor's or Master's degree in a related field. Experience with cloud platforms like AWS and data visualization tools is preferred. Join our innovative team to drive AI solutions!

Qualifications

• 2+ years of hands-on experience in Data Engineering, Machine Learning, or AI solution development.
• Experience with data pipelines using Airflow, Databricks, AWS Glue, or Apache Spark.
• Proficient in deploying models through REST APIs and serverless platforms.

Responsibilities

• Design, build, and maintain data pipelines and ETL/ELT workflows.
• Develop, train, validate, and deploy machine learning and AI models.
• Collaborate with cross-functional teams to translate analytical requirements into production-grade models.

Skills

Data Engineering

Machine Learning

AI Development

Python

SQL

Data Manipulation Libraries (Pandas, NumPy, PySpark)

Cloud Platforms (AWS, Azure, GCP)

Data Visualization Tools

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field

Tools

TensorFlow

PyTorch

Apache Airflow

Docker

Kubernetes

Job description

Job Description

Roles & Responsibilities

• Design, build, and maintain data pipelines and ETL/ELT workflows for structured and unstructured data sources.
• Develop, train, validate, and deploy machine learning and AI models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Collaborate with data engineers, business analysts, and product managers to translate analytical requirements into production-grade models and APIs.
• Optimize data processing performance and model inference pipelines for scalability and cost‑efficiency (preferably on cloud platforms such as AWS, Azure, or GCP).
• Work with data visualization and BI teams to enable analytics dashboards that surface insights from AI models.
• Ensure data quality, governance, and compliance with organizational and regulatory standards.
• Communicate complex technical outcomes to non-technical stakeholders with clarity and impact.

Required Skills and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.
• 2+ years of hands‑on experience in Data Engineering, Machine Learning, or AI solution development.
• Proficiency in Python, SQL, and data manipulation libraries such as Pandas, NumPy, or PySpark.
• Experience with data pipelines using Airflow, Databricks, AWS Glue, or Apache Spark.
• Strong understanding of ML algorithms (supervised, unsupervised, NLP, deep learning) and experience with at least one deployment‑ready framework (TensorFlow / PyTorch).
• Experience deploying models through REST APIs, containers (Docker, Kubernetes), or serverless platforms (AWS Lambda, Azure Functions).
• Familiarity with cloud‑based data platforms – AWS (S3, Redshift, SageMaker), Azure (Synapse, ML Studio), or GCP (BigQuery, Vertex AI).
• Understanding of data governance, metadata management, and data security best practices.
• Strong communication and collaboration skills, capable of engaging with both business and technical teams.
• Proven ability to deliver in agile environments and manage competing priorities effectively.

Preferred / Good‑to‑Have Skills

• Experience with LLMs, Generative AI, or prompt engineering for text/image applications.
• Knowledge of data versioning (DVC) and feature stores for ML pipelines.
• Exposure to data visualization tools (Tableau, Power BI, Looker).
• Understanding of DevOps/MLOps CI/CD for model deployment.
• Certification in AWS AI/ML Specialty, Azure Data Scientist, or Google Cloud ML Engineer.

Key Attributes

• Strong analytical mindset with attention to detail.
• Curious and self‑driven to explore emerging AI technologies.
• Effective communicator who can explain data and model insights to leadership.
• Team player with a focus on knowledge sharing and continuous learning.