SEO Executive

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

Design Engineer: 

Number of Positions: 01                  

Education Required: DME, BE Mechanical

Experience: 4-5 Years’    

Salary: negotiate at the time of the interview

Notice Period: Immediate joiner can be preferred

Background required for Manufacturing of Heat Exchanger, pressure vessel & Heavy fabrication Industries.

Job Description:

1.  Review of customer specification

2.  Mechanical Design on PV Elite software

3.  Mechanical design preparation for the 'U' stamp job

4.  Preparation of Fabrication drawing

5. Preparation of work order part list and enquiries required for material procurement

6.  Preparation of material standard specification as per ASME required for U-stamp job

7.  Checking of fabrication drawing, BOM

8.  Knowledge of ASME, TEMA, and PED is required

9.  Preparation of MDR

10. Interaction with AI, the client 

Responsibilities:

·       Collaborate with the marketing team to create engaging and relevant email content that aligns with the company's brand and marketing objectives.

·       Assist in the end-to-end execution of email campaigns, including building and testing email templates, managing distribution lists, and scheduling sends.

·       Help in segmenting the email database based on audience preferences, demographics, and behavior to deliver targeted and personalized messages.

·       Conduct A/B tests on subject lines, content, and design elements to optimize email performance and enhance open and click-through rates.

·       Analyze email campaign metrics and provide insights to improve future campaigns, focusing on key performance indicators (KPIs) such as conversion rates and ROI.

·       Ensure the accuracy and hygiene of the email database, performing regular data cleansing and list segmentation.

·       Stay updated with email marketing best practices and ensure compliance with relevant email regulations and data protection laws.

·       Support implementing and maintaining email automation workflows, nurturing leads, and enhancing customer engagement.

·       Coordinate with cross-functional teams, including design and content teams, to ensure seamless execution of email campaigns.

·       Prepare regular reports on email campaign performance and present findings to the marketing team, identifying areas for improvement.

Requirements:

·       Bachelor's degree in Marketing, Communications, or a related field.

·       2 years of experience in email marketing or related digital marketing roles.

·       Strong understanding of email marketing principles, best practices, and industry trends.

·       Familiarity with email marketing platforms and tools (e.g., Mailchimp, HubSpot, etc.).

·       Proficiency in analyzing email metrics and interpreting data to drive actionable insights.

·       Excellent written and verbal communication skills with a keen eye for detail.

·       Basic HTML and CSS knowledge for email template customization is a plus.

·       Ability to manage multiple tasks and meet deadlines in a fast-paced environment.

Responsibilities

• Reaching out to architects and interior designers according a marketing strategy
• Managing company’s communication related to business development
• Representing the company at events
• Engaging the retail customers through marketing campaigns

Skills Required

• Desktop applications like MS Office
• Fluency in English
• Knowledge of online channels of marketing and publicity

Qualification

• Graduate in any discipline

Experience

• Minimum 3 year of experience in digital marketing

Selected candidates day-to-day responsibilities include:

1. Working on computer vision/image processing applications like object classification, segmentation, etc.
2. Working on deep learning algorithms for machine vision based inspection usecases
3. Working on Machine Vision Cameras involving variety of Lens, Filters and other Optical Elements to collect data
4. Having full stack development experience will be plus