Data Innovator

4 days ago

Bellary, Karnataka, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000
High Performance Data Solutions Engineer

We are seeking an experienced Data Solutions Engineer to design and develop scalable data pipelines, integrate AI/ML models, and ensure low-latency processing of high-volume workloads.


Key Responsibilities:
  1. Data Pipelines: Build high-throughput, low-latency pipelines to process massive datasets efficiently. Ensure pipelines can handle 5–10 TB of structured and unstructured data at scale.
  2. Data Filtering & Curation: Optimize data ingestion and transformation for downstream models. Implement intelligent scanning mechanisms to filter out relevant data for AI/ML models.
  3. AI/ML Integration: Leverage GenAI models under the Vertex AI umbrella. Build and fine-tune custom models when LLMs are cost-prohibitive or less effective.
  4. Cloud Infrastructure: Architect scalable solutions primarily on GCP (Vertex AI, BigQuery, GKE, Cloud run, PostgreSQL, Dataflow, Pub/Sub). Azure knowledge is a plus but not mandatory.
  5. Performance Optimization: Ensure real-time, low-latency processing for high-volume workloads. Optimize GPU/CPU-intensive environments to manage cost and efficiency.
  6. Collaboration & Ownership: Work closely with data scientists, ML engineers, and solution architects. Take end-to-end ownership of assigned tasks and deliverables, working independently where needed.
Required Skills & Qualifications:
  1. Programming: Expert-level Python (mandatory).
  2. Data Engineering: Hands-on experience with streaming pipelines, and large-scale data ingestion frameworks.
  3. AI/ML Expertise: Experience integrating and fine-tuning LLMs and GenAI models. Comfortable working with custom model development where LLMs cannot be applied.
  4. Cloud: GCP (mandatory) — experience with Vertex AI, BigQuery, GKE, Cloud Run, PostgreSQL, Dataflow, Pub/Sub, etc.
  5. Scalability & Low Latency: Proven ability to design and implement high-performance, distributed data solutions.
Benefits:
  • Design and implement high-performance, distributed data solutions
  • Work closely with data scientists, ML engineers, and solution architects

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