Katalytx
I
C a t a l y z i n g g r o w t h
AI/ML : Engineers & Architect
Chennai
Immediate
3+ yrs exp
Key Responsibilities
-
Design, develop, train, and deploy machine learning (ML) and deep learning (DL) models for life sciences and manufacturing use cases.
-
Collaborate with cross-functional teams to identify opportunities for AI/ML-driven automation and optimization.
-
Implement end-to-end ML pipelines – from data ingestion and feature engineering to model training, validation, and deployment.
-
Work with big data platforms (Databricks, Snowflake, AWS Sagemaker, Azure ML, etc.) to manage and process large-scale datasets.
-
Develop NLP, computer vision, or predictive analytics models for applications in research, digital labs, and customer analytics.
-
Collaborate with software engineering teams to productionize and integrate AI models into enterprise applications.
-
Conduct performance tuning, model monitoring, and continuous retraining as needed.
-
Stay updated with emerging trends in AI/ML technologies and tools.
Required Skills and Qualifications
-
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.
-
Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost, or LightGBM.
-
Strong understanding of data structures, algorithms, and statistics.
-
Experience with cloud-based ML platforms – AWS SageMaker, Azure ML, or GCP Vertex AI.
-
Hands-on experience in MLOps – model versioning, CI/CD, and monitoring using tools like MLflow, Kubeflow, or Airflow.
-
Exposure to NLP, computer vision, or time-series forecasting techniques.
-
Excellent problem-solving, communication, and collaboration skills.
Preferred Qualifications
-
Experience in Life Sciences / Healthcare / Pharma / Biotech domains.
-
Familiarity with data engineering tools like Databricks, Apache Spark, or Snowflake.
-
Knowledge of GenAI and LLM fine-tuning (e.g., OpenAI, Hugging Face, LangChain).
-
Experience deploying models as REST APIs or microservices using Flask/FastAPI.
-
Understanding of data governance, model ethics, and regulatory compliance in AI applications.
-
Work on impactful projects driving innovation in healthcare and life sciences.
-
Collaborate with global teams across R&D, engineering, and data science.
-
Access to cutting-edge AI/ML platforms and technology ecosystem.
-
Inclusive, diverse, and innovation-driven culture.
Expert
Python, Tensorflow, PyTorch, XGBoost
Sr. Data Engineer – AWS Databricks / Data Tech Lead – AWS Databricks
Chennai
Immediate
Key Responsibilities
-
Data Pipeline Development: Design and implement robust ETL/ELT pipelines using Databricks, PySpark, and Delta Lake to process structured and unstructured data efficiently.
-
Manage job orchestration, scheduling, and workflow automation through Databricks Workflows or Airflow.
-
Performance Optimization: Tune and optimize Databricks clusters and notebooks for performance, scalability, and cost-efficiency.
-
Data Governance: Implement data governance and lineage using Unity Catalog and other platform-native features
-
Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
-
Cloud Integration: Leverage cloud platforms (AWS) to build and deploy data solutions, ensuring seamless integration with existing infrastructure.
-
Data Modeling: Develop and maintain data models that support analytics and machine learning workflows.
-
Automation & Monitoring: Implement automated testing, monitoring, and alerting mechanisms to ensure data pipeline reliability and data quality.
-
Documentation & Best Practices: Maintain comprehensive documentation of data workflows and adhere to best practices in coding, version control, and data governance.
Required Qualifications
-
Experience: 5+ years in data engineering, with hands-on experience using Databricks and Apache Spark.
-
Programming Skills: Proficiency in Python and SQL;
-
Cloud Platforms: Strong experience with cloud services such as AWS (e.g., S3, Glue, Redshift
-
Data Engineering Tools: Familiarity with tools like Airflow, Kafka, and dbt.
-
Data Modeling: Experience in designing data models for analytics and machine learning applications.
-
Collaboration: Proven ability to work in cross-functional teams and communicate effectively with non-technical stakeholders.
Primary Skill Set
Databricks, Apache Spark/Pyspark, Python, SQL, ETL/ELT development, Delta Lake, Cloud platforms (AWS), Data modeling, Cross-functional collaboration, Communication
Secondary Skill Set
Airflow, dbt, Kafka, Hadoop, MLflow, Unity Catalog, Delta Live Tables, Cluster optimization, Data governance, Security and compliance, Databricks certifications
5+ yrs exp
Expert
AWS, Databricks
Send your resume to katalytx@gmail.com.
Subject - AI ML Engineer/ Architect