AI-ML Data Engineer Job ID: 324609

CoreFlex Solutions Inc.; Pune District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A leading technology solutions company located in Pune is seeking a Data Engineer with expertise in building and maintaining data pipelines and deploying machine learning models. The candidate should possess a Bachelor's or Master's degree in a related field and 2+ years of experience in data engineering and AI solutions. Strong skills in Python, SQL, and cloud platforms like AWS are essential for success in this role.

Qualifications

• 2+ years of hands-on experience in Data Engineering, Machine Learning, or AI solution development.
• Strong understanding of ML algorithms (supervised, unsupervised, NLP, deep learning).
• Proven ability to deliver in agile environments and manage competing priorities effectively.

Responsibilities

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

Skills

Python

SQL

Data Engineering

Machine Learning

Data manipulation libraries (Pandas, NumPy, PySpark)

Airflow

AWS

Docker

Kubernetes

Cloud platforms (AWS, Azure, GCP)

Education

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

Tools

TensorFlow

PyTorch

Apache Spark

Databricks

AWS Glue

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.