10 months ago
Pune, India or Bengaluru, IndiaSenior
Responsibilities
- Design, develop, and maintain scalable data pipelines for ingestion, transformation, feature stores, model-training workflows, and real-time inference services.
- Design and optimize ETL/ELT pipelines and data structures in Snowflake or Redshift for business intelligence.
- Build workflows for storing and retrieving semantic representations of unstructured data for search and retrieval.
- Implement analytics and dashboarding solutions with natural-language query and AI-backed insight capabilities.
- Manage prompt-engineering techniques, orchestration flows, and model fine-tuning routines for conversational interfaces.
- Oversee vector data stores and indexing methodologies for retrieval-augmented generation workflows.
- Partner with stakeholders to gather requirements for language-model initiatives and translate them into scalable solutions.
- Document data processes, workflows, and model-deployment routines.
- Stay current with data engineering, MLOps, and LLM operations methodologies.
Requirements
- 6–7+ years of experience building scalable data infrastructure as a senior data engineer.
- 1–2 years of hands-on exposure to AI/ML workflows.
- Hands-on experience with Apache Spark, Hadoop, and Kafka for distributed processing and real-time ingestion.
- Experience building pipelines from RDBMS, JSON, APIs, and flat-file sources.
- Advanced SQL and PL/SQL skills, business intelligence and data warehouse expertise, and experience with relational databases and cloud database services such as Snowflake or Redshift.
- Experience using Python for data engineering, transformation, advanced data manipulation, and large-scale processing.
- Deep understanding of vector databases and RAG architectures.
- Experience integrating open-source LLM frameworks into model training, customization, and scalable inference workflows.
- Experience with AWS or Azure Machine Learning for managed LLM deployments.
- Understanding of software engineering principles and experience with Unix, Linux, or Windows operating systems.
- Experience with version control, code repositories, branching, merging, and distributed development collaboration.
- Strong English communication skills and interest in business operations and data-driven decision-making.
- Preferred experience with DataStax AstraDB, LangChain, LlamaIndex, prompt engineering, RAG, intelligent workflow orchestration, Hugging Face Transformers, LLaMA-4, fine-tuning, inference optimization, MLOps tooling, and CI/CD pipelines.
Benefits
- Remote work opportunity for applicants in India.
- B2B employment with gross compensation or a full-time employment option.
- Stable long-term employment with growth opportunities.
- Competitive salary with annual performance reviews.
- Company-provided hardware.
- Professional training, seminars, and conference compensation.
- Referral program.
- Company-supported English classes.
- The interview process is conducted in English.
Tech Stack
Amazon RedshiftApache HadoopApache KafkaApache SparkAWSHugging Face TransformersLinuxPythonSnowflakeSQLWindows
Categories
AI ApplicationsData Engineering
