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Open nowPosted 305 days ago

AI Lead Developer

Scrabble & Jigsaw

Where
gurgaon, Andaman and Nicobar Islands, India
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Your applicationOpen nowAI Lead DeveloperScrabble & Jigsaw · gurgaon, Andaman and Nicobar Islands, India

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 305 days ago

The posting

Company: Ethara.AI

Location: 5th Floor, Plot No. 273, Udyog Vihar II Rd, Udyog Vihar Phase 1, Sector 20, Gurugram,

Haryana 122016

About us

Ethara AI is a leading AI and data services company in India, specializing in building high-quality, domain-

specific datasets for Large Language Model (LLM) fine-tuning. Our work bridges the gap between

academic learning and real-world AI applications, and we are committed to nurturing the next

generation of AI professionals.

Role Overview

We are seeking an experienced AI Lead Developer to architect, build, and scale advanced AI/ML

solutions across our product portfolio. The ideal candidate has deep hands-on expertise in machine

learning, large language models (LLMs), modern MLOps practices, and end-to-end AI system design. This

individual will lead technical decision-making, mentor the engineering team, and ensure our AI

initiatives meet high standards of performance, reliability, and business alignment.

Key Responsibilities

AI Architecture & Development

 Lead the design and development of production-grade AI/ML systems, including model

selection, training pipelines, evaluation frameworks, and deployment workflows.

 Architect solutions using LLMs, multimodal models, and advanced deep learning approaches.

 Build scalable, fault-tolerant pipelines for data ingestion, preprocessing, feature engineering,

and model serving.

 Drive adoption of best-practice MLOps methodologies (CI/CD for ML, monitoring, drift

detection, versioning, automated retraining).

Technical Leadership

 Provide hands-on mentorship to AI engineers, ML developers, and data scientists.

 Lead code reviews, set engineering standards, and ensure technical excellence across AI

initiatives.

 Evaluate new AI technologies, frameworks, and tooling (LLM providers, vector DBs, inference

engines, model optimization techniques).

 Collaborate with cross-functional teams (Product, Data, DevOps, Cloud Engineering) to align AI

capabilities with business goals.Model Performance & Optimization

 Improve inference performance through quantization, distillation, pruning, and GPU/TPU

optimization.

 Design and implement robust evaluation metrics, benchmarking processes, and model

monitoring systems.

 Optimize cost-performance trade-offs across training and inference environments.

Project Execution & Delivery

 Translate business requirements into technical AI solution designs.

 Own delivery timelines, resource estimation, and execution for AI features and projects.

 Ensure compliance with responsible AI, data governance, and security frameworks.

Required Qualifications

 3+ years of hands-on experience in AI/ML development, with at least 2–3 years in a lead or

senior role.

 Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.

 Experience building and shipping production-grade AI/ML systems at scale.

 Excellent understanding of LLMs, transformers, vector databases, prompt engineering, and

model fine-tuning.

 Experience with cloud AI platforms (AWS Sagemaker, GCP Vertex AI, Azure ML) and

containerization (Docker/Kubernetes).

 Solid grounding in data structures, distributed computing, and system design.

 Strong understanding of MLOps tools (MLflow, Kubeflow, Weights & Biases, Airflow, Ray).

Preferred Skills

 Experience with RAG pipelines, custom model training, and evaluation of multimodal systems.

 Knowledge of CUDA, GPU optimization, and model acceleration frameworks (TensorRT, ONNX

Runtime).

 Experience integrating AI into enterprise systems, APIs, or microservices architectures.

 Background in NLP, CV, reinforcement learning, or generative AI applications.

 Familiarity with responsible AI guidelines, compliance frameworks, and data privacy regulations.

Soft Skills

 Strong leadership and communication capabilities.

 Ability to manage ambiguity and drive clarity in fast-paced environments.

 Proven ability to collaborate across engineering, research, and business teams.

 Strategic thinking with an execution mindset.Education

 Bachelor’s or Master’s degree in Computer Science, Data Science, Art

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