Data Science & Engineering Lead

Particle41; Pune District, Pimpri-Chinchwad; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Particle41 seeks a Data Science & Engineering Lead to build and deploy high-impact ML models, optimize data systems, and drive insights. You’ll work hands-on with Databricks, Spark, and Azure, guiding a talented team through end-to-end model development and production.

The role demands leadership, 7+ years in data science or data engineering, and strong cloud, MLOps, and BI experience to deliver scalable, data-driven solutions.

Qualifications

• Bachelor's degree in a related field; Master’s/PhD preferred
• 7+ years of experience in data science, ML, or data engineering
• Strong leadership and cross-functional collaboration
• Proven expertise in both supervised and unsupervised ML and deep learning

Responsibilities

• Design and implement ML models for real-world business problems
• Lead model development for neural architectures (CNN, RNN, Transformers)
• Advance NLP with NLTK and language models
• Develop computer vision models with OpenCV
• Oversee time-series forecasting and anomaly detection
• Develop lakehouse architectures and scalable data pipelines
• Lead ETL with Airflow, DBT, Airbyte
• Design OLTP/OLAP databases using Snowflake, SQL Server, PostgreSQL, MySQL
• Build NoSQL solutions (MongoDB, DynamoDB, ElasticSearch)
• Lead cloud infra on AWS or Azure; manage MLOps with Sagemaker, Databricks, Azure ML Studio
• Develop BI dashboards (Tableau, QuickSight, PowerBI) for insights
• Implement GPU acceleration and CUDA training
• Mentor junior team members in AI/ML techniques

Skills

Supervised ML

Unsupervised ML

Deep learning

ML model deployment

MLOps

Data pipelines

Lakehouse

ETL design

Cloud architectures

Team leadership

Mentoring

Data visualization

Python

Big data

SQL/NoSQL

Distributed systems

Education

Bachelor's degree

Master's degree

PhD

Tools

Databricks

Spark

Azure

AWS

OpenCV

NLTK

Langchain

Huggingface

OpenAI

Snowflake

SQL Server

PostgreSQL

MySQL

MongoDB

DynamoDB

ElasticSearch

Airflow

DBT

Airbyte

Kinesis

Kafka

Terraform

CloudFormation

Delta

Iceberg

Sagemaker

Databricks ML

Azure ML Studio

Tableau

PowerBI

QuickSight

Job description

Lead the charge in AI and data innovation as our Data Science & Engineering Lead. Here, you'll work hands-on with our talented team to build and deploy high-impact ML models, optimize our data systems, and drive actionable insights. If you're skilled in advanced AI tools like Databricks, Spark, and Azure, and excited to push boundaries in machine learning and engineering, we want you on our team. Join us for meaningful work, a collaborative culture, and competitive benefits.

In This Role, You Will:

• Design and implement supervised and unsupervised ML models (e.g., OLS, Logistic Regression, Ensemble Methods) to solve real-world business problems.
• Lead model development for advanced architectures in neural networks, such as ANN, CNN, RNN, GAN, Transformers, and RESNet.
• Drive NLP advancements with tools like NLTK and neural-based language models.
• Oversee the development of computer vision models, utilizing OpenCV for real-world applications.
• Lead time-series modeling projects for forecasting and anomaly detection.
• Utilize AI techniques like Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to enhance model performance.
• Build and maintain scalable data pipelines for both streaming and batch processing.
• Architect and optimize lakehouse solutions using Delta/Iceberg and bronze-silver-gold architectures.
• Lead the development of ETL processes with tools like Airflow, DBT, and Airbyte to support data flow and transformation.
• Design and optimize database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL.
• Develop NoSQL solutions, leveraging MongoDB, DynamoDB, and ElasticSearch for unstructured data.
• Lead efforts in building cloud infrastructure, particularly in AWS (preferred) or Azure, using services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka.
• Oversee MLOps pipelines for robust deployment of ML models in production with platforms like Sagemaker, Databricks, and Azure ML Studio.
• Develop and optimize business intelligence dashboards with tools like Tableau, QuickSight, and PowerBI for actionable insights.
• Implement GPU acceleration and CUDA for model training and optimization.
• Mentor junior team members in cutting-edge AI/ML techniques and best practices.

Skills and Experience We Value:

• Proven expertise in both supervised and unsupervised ML, advanced deep learning, including TensorFlow, PyTorch, and neural network architectures (e.g., CNN, GAN, Transformers).
• Hands-on experience with machine learning libraries and tools such as Scikit-learn, Pandas, and Numpy.
• Proficiency in AI model development using LLM libraries (e.g., Langchain, Huggingface, OpenAI).
• Strong MLOps skills, with experience deploying scalable pipelines in production using tools like Sagemaker, Databricks, and Azure ML Studio.
• Advanced skills in big data frameworks like Apache Spark, Glue, and EMR for distributed model training.
• Expertise in ETL processes and data pipeline development with tools like Airflow, DBT, and Airbyte.
• Strong knowledge in lakehouse architectures (Delta/Iceberg) and experience with data quality frameworks like Great Expectations.
• Proficiency in cloud platforms (AWS preferred or Azure), with a deep understanding of services like IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.
• Proficiency with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation for automation.
• Advanced skills in GPU acceleration, CUDA, and distributed model training.
• Demonstrated ability to architect and deploy scalable machine learning and data-intensive systems.
• Proficiency in database modeling for OLTP/OLAP systems and expertise with relational and NoSQL databases.
• Strong mentoring skills, with a proven track record of guiding junior team members in AI/ML best practices.
• Bachelor's degree in a related field (required), with a Master's or PhD in Data Science or a related field (preferred).
• 7+ years of experience in data science, machine learning, or data engineering.
• AWS or Azure certification (strongly preferred).
• Strong communication and leadership skills with experience working cross-functionally to deliver high-impact data solutions.

About Particle41

Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do to achieve the ultimate outcomes for our clients. Empowering Leadership for Innovation in Teamwork with Excellence ( ELITE )

• E - Empowering: Enabling individuals to reach their full potential.
• L - Leadership: Taking initiative and guiding each other toward success.
• I - Innovation: Embracing creativity and new ideas to stay ahead.
• T - Teamwork: Collaborating with empathy to achieve common goals.
• E - Excellence: Striving for the highest quality in everything we do.

We seek team members who embody these values and are committed to contributing to our mission. Particle41 welcomes individuals from all backgrounds who are committed to our mission and values. We provide equal employment opportunities to all employees and applicants, ensuring that hiring and employment decisions are based on merit and qualifications without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. This policy applies to all aspects of employment and hiring.