AI / ML Engineer

DataPhi; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

DataPhi in Pune, India is seeking an AI Engineer to design, develop, and deploy AI-driven solutions at scale. You will work with cross-functional teams to move models from research to production, ensuring performance, fairness, and explainability.

You will also collaborate on data handling, model monitoring, and continuous improvement, while applying best practices in ML ops and scalable deployment.

Qualifications

• Three or more years of experience applying AI to real-world technology solutions.
• Experience with LLMs, prompt engineering and tuning.
• Experience deploying models in cloud environments (e.g., SageMaker, Vertex AI), MLOps and APIs.
• Experience with data engineering basics and building data pipelines.
• Excellent written and verbal communication skills.

Responsibilities

• AI model development: design and implement models using ML, DL, NLP, and computer vision.
• Train, test, fine-tune, and optimize AI models for accuracy and scalability.
• Deploy AI solutions into production environments via APIs, Docker, and Kubernetes.
• Collect, analyze, and interpret large datasets for model training.
• Collaborate with data scientists, software engineers, PMs, and stakeholders to align AI strategy with business goals.
• Monitor model performance in real-time and implement continuous improvements (MLOps).

Skills

AI development

LLM & prompt engineering

Feature engineering pipelines

MLOps & cloud deployment

REST API development

Python programming

Data engineering basics

Data pipelines

Communication skills

NoSQL/RDBMS knowledge

Docker & Kubernetes

Model evaluation & monitoring

Education

Bachelor’s or Master’s in CS or related field

Tools

SageMaker

Vertex AI

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

Hadoop

Spark

REST APIs

NoSQL databases

RDBMS

Job description

We are seeking a highly skilled and motivated AI Engineer to join our growing team. In this role, you will design, develop, and deploy AI driven solutions that solve real-world problems at scale. You will collaborate with cross-functional teams to transition models from research to production, ensuring performance, fairness, and explainability.

Key Responsibilities

• AI Solution Development: Design and develop AI models and algorithms from scratch, utilizing techniques like machine learning, deep learning, natural language processing (NLP), and computer vision.
• Model Management: Train, test, fine-tune, and optimize AI and machine learning models for performance, accuracy, and scalability.
• Deployment and Integration: Deploy AI solutions into production environments using APIs, microservices, Docker, and Kubernetes. Integrate these AI capabilities with existing software systems and applications
• Data Handling: Collect, analyze, and interpret large, complex datasets to derive insights and ensure data integrity for model training.
• Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to define project goals and align AI strategies with business objectives.
• Monitoring and Maintenance: Manage the AI development process (MLOps), monitor model performance in real-time, troubleshoot issues, and implement continuous improvements.

Skills & Experience: Key Requirements

Required skills

• Three or more years of experience in applying AI to practical and comprehensive technology solutions
• Working with LLM and prompt engineering and prompt tuning
• Experience in Implementing pipelines for feature engineering and model retraining
• Experience in Collaborating with data scientists to transition models from research to production
• Experience in Managing model deployment in cloud environments (e.g. SageMaker, Vertex AI), MLOps and APIs
• Experience in Testing and validating AI performance across use cases.
• Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns
• Experience in basics of data engineering and building data pipelines
• Experience in REST API development, NoSQL database design, and RDBMS design and optimizations.
• Excellent written and verbal communication skills.

Good to Have:

• Experience of applying AI in real-time or large-scale systems
• Understanding of privacy, bias, and AI risk considerations
• Experience with innovation accelerators
• Experience with cloud environments
• Daat storytelling and model explainability
• Experience in model tuning, monitoring, and improvement
• Experience in Ensuring models is secure, fair, and explainable
• Proficiency in programming languages like Python (essential), Java, or C++.
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with MLOps, cloud platforms (AWS, Azure, GCP), and big data technologies (Hadoop, Spark).
• Knowledge of REST API development and database design.
• Expertise in specific AI domains like NLP, computer vision, or generative AI (LLMs, RAG).

Qualifications

Bachelor’s or master’s degree in computer science or related field.