AI Engineer

Industry & Sector: HR Technology / Talent Solutions — building AI-driven products and analytics that automate talent discovery, candidate matching, and workforce intelligence for enterprise customers. This is an on-site engineering role based in India focused on production-grade AI/ML systems for the HR domain.

Primary standardized title: Machine Learning Engineer

About The Opportunity

We are hiring an AI Engineer to design, build, and productionize intelligent models and services that power next-generation recruitment and HR automation. You will work on end-to-end ML lifecycle tasks — from data preparation and model development to deployment, monitoring, and continuous improvement — in an on-site delivery environment.

Role & Responsibilities

• Design and implement scalable ML/NLP models (classification, ranking, embeddings, LLM pipelines) that solve HR-specific problems like candidate matching, resume parsing, and semantic search.
• Build reliable model deployment pipelines and production services (APIs, batch/streaming pipelines) with observability, automated testing, and rollback strategies.
• Collaborate with product and data teams to translate business requirements into data-driven solutions and measurable KPIs.
• Optimize model performance for latency, throughput, and cost—apply quantization, pruning, distillation and GPU/CPU optimizations where required.
• Implement MLOps best practices: CI/CD for models, versioning, monitoring for drift, automated retraining pipelines and alerting.
• Document solutions, enforce code quality, and mentor junior engineers to raise engineering standards across the team.
  
  

Skills & Qualifications

Must-Have

• Strong software engineering experience with Python and production ML frameworks (PyTorch or TensorFlow).
• Practical experience with NLP and transformer-based models (Hugging Face Transformers) for tasks like NER, classification, semantic search, or summarization.
• Hands-on experience deploying models as services (REST APIs), containerizing with Docker and orchestrating with Kubernetes.
• Experience deploying and operating models on cloud platforms (AWS preferred) and familiarity with cloud networking and storage patterns.
• Proven track record of taking models to production: CI/CD for ML, model versioning, monitoring, and automated retraining.
• Strong debugging and performance-tuning skills for model inference (latency, memory, GPU utilization).
  
  

Preferred

• Experience with MLOps tools: MLflow, Kubeflow, or similar orchestration and experiment-tracking frameworks.
• Previous exposure to Large Language Models (LLMs) and prompt engineering or agentic workflows.
• Domain experience in HRTech, recruitment systems, or enterprise search products.
  
  

Benefits & Culture Highlights

• On-site role with a high-impact engineering culture and direct collaboration with product & data science teams.
• Opportunity to work on cutting-edge NLP/AI systems and influence product direction in the HRTech space.
• Competitive compensation, professional development, and fast career growth for high performers.
  
  

Location: India (On-site). Keywords: AI Engineer, Machine Learning, NLP, Deep Learning, Model Deployment, MLOps, PyTorch, TensorFlow, Hugging Face, Docker, Kubernetes, AWS, REST APIs.

Skills: ai ml,aws,data scientist,kubernetes,python,ai engineer,tensorflow,docker,pytorch