About the Opportunity :
We are seeking a highly skilled Lead / Senior Engineer Python / Data / AI to design and build large-scale data-driven systems and AI-powered solutions.
This is a hands-on technical leadership role that combines the depth of Python development, data engineering, and machine learning expertise with the architectural understanding of cloud-native AI platforms.
The ideal candidate will bring experience in developing scalable data pipelines, deploying ML models, and applying modern AI frameworks (TensorFlow, PyTorch) to solve business problems.
This position offers the chance to contribute to full-stack AI solution design from data ingestion to model training and deployment in a dynamic, innovation-focused environment.
What Youll Do :
- Design, develop, and maintain data engineering pipelines using Python, PySpark, and SQL for structured and unstructured data.
- Build, train, and optimize machine learning and deep learning models using TensorFlow and PyTorch.
- Implement scalable data solutions across cloud environments such as Azure, AWS, or GCP.
- Collaborate with data scientists and product teams to productionize ML models and ensure smooth deployment through MLOps pipelines.
- Architect and implement ETL / ELT processes that ensure data quality, security, and compliance.
- Perform feature engineering, data validation, and performance tuning to enhance model efficiency and accuracy.
- Leverage distributed computing frameworks (Spark, Databricks, or similar) for large-scale data processing.
- Collaborate closely with software engineers, data analysts, and business stakeholders to translate analytical insights into scalable applications.
- Define best practices for data pipelines, version control, and CI / CD automation within the AI / ML lifecycle.
- Stay current with emerging technologies in AI, data engineering, and MLOps, and recommend their adoption when appropriate.
What You Bring :
5 to 12 years of hands-on experience in Python development, data engineering, and machine learning.Strong proficiency in Python, SQL, and PySpark, with experience in building end-to-end data workflows.Expertise in one or more AI / ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proven experience with data modeling, ETL / ELT design, and data pipeline orchestration in production environments.Solid understanding of cloud computing platforms Azure, AWS, or GCP including data and AI services.Knowledge of MLOps practices, model deployment strategies, and CI / CD pipelines for ML workflows.Familiarity with distributed computing and big data frameworks (Spark, Databricks, or Hadoop).Strong problem-solving and debugging skills with a focus on data quality, scalability, and performance optimization.Excellent communication and leadership skills to mentor junior engineers and collaborate across technical and business teams.Bachelors or Masters degree in Computer Science, Data Science, or a related engineering discipline.Preferred Skills :
Exposure to Generative AI (LLMs, embeddings, prompt engineering) or NLP pipelines.Familiarity with containerization (Docker, Kubernetes) and serverless ML deployments.Experience in data versioning and model monitoring tools such as MLflow, DVC, or Kubeflow.Understanding of streaming data systems (Kafka, Kinesis) and real-time analytics architectures.Prior experience working with cross-functional data science teams on AI-driven products(ref : hirist.tech)