AI/ML Data Engineer
- Synechron
- 6 - 11 years
- Bengaluru
- 5 days ago
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Job Description
Job Summary
Synechron is seeking an experienced AI/ML Data Engineer specialized in processing unstructured data and integrating advanced language models within enterprise environments. This role involves designing scalable data pipelines, implementing document cleansing, classification, and enrichment, and supporting Retrieval-Augmented Generation (RAG) architectures. The successful candidate will bridge data engineering and AI development to enable intelligent, AI-first applications that enhance decision-making and operational efficiency.
Synechron is seeking an experienced AI/ML Data Engineer specialized in processing unstructured data and integrating advanced language models within enterprise environments. This role involves designing scalable data pipelines, implementing document cleansing, classification, and enrichment, and supporting Retrieval-Augmented Generation (RAG) architectures. The successful candidate will bridge data engineering and AI development to enable intelligent, AI-first applications that enhance decision-making and operational efficiency.
Software Requirements
- Required:
- Strong proficiency in Python (latest stable version) for building data pipelines and implementing ML workflows
- Hands-on experience with PySpark for distributed data processing and large-scale ETL workflows
- Experience processing unstructured data such as PDFs, texts, emails, and forms, including OCR and NLP techniques
- Familiarity with NLP frameworks and libraries such as Transformers, Hugging Face, LangChain, and FAISS
- Working knowledge of vector databases such as Redis or similar for semantic search and retrieval
- Understanding of LLM lifecycle management, including fine-tuning, inference, and prompt engineering
- Experience working with CI/CD practices, Git, and version control tools for data projects
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Preferred:
- Experience with cloud platforms like GCP, AWS, or Azure, supporting data pipeline deployment
- Knowledge of data quality metrics and data governance best practices
- Exposure to data orchestration tools such as Apache Airflow or Prefect
Overall Responsibilities
- Build and maintain scalable, robust data pipelines for unstructured content, ensuring high data quality and performance efficiency
- Develop algorithms for document classification, cleansing, and enrichment to feed AI/ML systems
- Integrate data workflows with LLM pipelines supporting RAG architectures for semantic search and Question-Answering (QA) systems
- Engineer and optimize vector embeddings, document chunking, and metadata tagging for AI applications
- Collaborate closely with AI architects, data scientists, and platform teams to design end-to-end AI solutions
- Implement automation, monitoring, and security best practices to ensure system reliability and compliance
- Support project lifecycle activities, including proof-of-concept, testing, deployment, and ongoing monitoring
- Share domain expertise, conduct knowledge sharing, and mentor team members
Technical Skills (By Category)
- Programming Languages:
Required: Python, PySpark
Preferred: SQL, Java, or other scripting languages for automation and integrations
- Databases Data Management:
NoSQL (Redis, MongoDB), relational databases (PostgreSQL, MySQL), data tagging, and metadata management
- Cloud Technologies:
GCP (BigQuery, Dataflow), AWS, or Azure for deployment, scaling, and storage support (preferred)
- Frameworks Libraries:
Transformers, Hugging Face, LangChain, FAISS, Spark MLlib, NLP libraries
- Development Orchestration Tools:
Git, Jenkins, CI/CD pipelines, Apache Airflow or Prefect (preferred)
- Operational Security Tools:
Monitoring platforms (Datadog, Prometheus), security best practices, data encryption
Experience Requirements
- Minimum of 6 years of professional experience in data engineering, with at least 2 years dedicated to unstructured data processing and AI/ML integration
- Proven success building scalable data pipelines supporting NLP, document classification, and semantic search
- Hands-on experience with vector databases, embedding models, and retrieval systems supporting RAG workflows
- Experience working with cloud platforms and performing data quality audits in enterprise environments
- Industry experience in financial services, healthcare, or enterprise AI applications is advantageous
Day-to-Day Activities
- Design, develop, and enhance data pipelines for unstructured data ingestion, processing, and enrichment
- Implement NLP models, document classification, and semantic search capabilities supporting RAG architectures
- Collaborate with data scientists, platform engineers, and stakeholders to address data and AI system needs
- Troubleshoot data pipeline issues, optimize query performance, and implement best practices for data security and governance
- Automate data workflows, manage infrastructure as code, and support cloud deployment strategies
- Monitor pipeline performance, ensure data quality, and document architecture and operational workflows
Qualifications
- Bachelors or Masters degree in Computer Science, Data Science, or a related field
- At least 6 years of experience in data engineering, focusing on unstructured data and AI model integration
- Strong expertise with Python, PySpark, NLP, and vector retrieval systems
- Certifications in cloud platforms or data engineering tools are preferred
- Proven ability to deliver high-quality, scalable, and secure data solutions in enterprise settings
Professional Competencies
- Strong analytical and troubleshooting skills for complex data and AI systems
- Effective communication skills to interface with technical and business stakeholders
- Leadership qualities to mentor team members and promote best practices in data engineering and AI
- Strategic thinking to design scalable, secure, and compliant AI data pipelines
- Adaptability to new tools, frameworks, and emerging AI/ML trends
- Time management skills to prioritize tasks and deliver solutions efficiently
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data Platform EngineerEmployement Type: Full timeContact Details:
Company: SynechronLocation(s): Bengaluru+ View Contact
Keyskills: data engineer vector search pyspark redis sql cloud java git postgresql data science gcp spark jenkins mysql mongodb ml architecture azure python airflow ai llm nosql nlp compliance aws infrastructure as code ai model
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