Lead AI/ML Engineer

Experience: 6–7 Years

Location: Whitefield, Bangalore

Employment Type: Full-Time (Onsite)

About Hithonix Solutions Pvt Ltd

Hithonix Solutions Pvt Ltd is a forward-thinking technology company delivering intelligent, scalable, and innovative software solutions that drive business growth. Built on values of quality, integrity, and excellence, we foster a collaborative culture that encourages innovation, continuous learning, and technical ownership. We work across domains such as e-commerce, fintech, health tech, and enterprise software, leveraging cutting-edge AI and cloud technologies to solve complex business problems.

Job Overview

We are seeking an experienced AI / ML Tech Lead to own the technical vision, architecture, and execution of our AI and Machine Learning initiatives. This is a hands-on leadership role where you will design scalable ML systems, lead end-to-end delivery of production-grade AI solutions, and mentor a team of AI/ML engineers.

You will play a critical role in building robust MLOps pipelines, deploying models at scale, and driving innovation in areas such as Generative AI, LLMs, RAG pipelines, and intelligent agents.

Key Roles & Responsibilities

Technical Leadership & Architecture

• Define and own end-to-end AI/ML system architecture including data pipelines, model training, deployment, serving, and monitoring
• Establish engineering standards, best practices, and coding guidelines for ML development and MLOps
• Make key architectural decisions related to frameworks, tools, cloud platforms, scalability, and security

• Lead the complete ML lifecycle: problem definition, data analysis, feature engineering, model development, evaluation, and deployment
• Ensure production readiness with focus on performance, reliability, explainability, security, and compliance
• Design monitoring, retraining strategies, and model/version lifecycle management

• Mentor and guide AI/ML engineers and data scientists through code reviews and technical coaching
• Delegate tasks, unblock technical challenges, and ensure timely delivery of milestones
• Act as the primary technical interface between product managers, data engineers, backend teams, and stakeholders

• Drive implementation of MLOps best practices including CI/CD, automated testing, experiment tracking, and monitoring
• Design and manage scalable ML deployments using Docker, Kubernetes, and cloud-native ML services
• Optimize cloud infrastructure for cost, performance, and reliability

• Lead research and adoption of Generative AI, LLMs, embeddings, RAG architectures, and agent-based systems
• Evaluate and introduce new tools, frameworks, and platforms to improve solution quality and team productivity
• Identify technical risks early and implement mitigation strategies

Required Skills & Experience

6+ years of professional experience in AI, Machine Learning, or Deep Learning

2+ years in a technical leadership, senior engineer, or architect role.

Technical Skills

• Strong proficiency in Python and ML/DL frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost
• Solid foundation in data structures, algorithms, probability, and statistics
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow
• Expertise with Docker, Kubernetes, and containerized ML deployments
• Experience with cloud platforms: AWS (SageMaker), Azure ML, or GCP Vertex AI
• Strong SQL skills; experience with Pandas, NumPy, and data preprocessing
• Proven experience deploying ML models via REST APIs (FastAPI / Flask)
• Hands-on exposure to NLP and/or Computer Vision use cases
• Strong understanding of LLMs, embeddings, RAG pipelines, and Generative AI
• Experience with Git, CI/CD pipelines, and data/model versioning
• Exposure to Spark, Databricks, or Hadoop is a plus

• Strong technical decision-making and analytical problem-solving skills
• Excellent communication skills with the ability to explain complex AI concepts to non-technical stakeholders
• Proven ability to mentor engineers and build high-performing teams
• Familiarity with Agile/Scrum development methodologies

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Engineering, or a related field
• Cloud or AI/ML certifications (AWS, Azure, GCP) are an added advantage

• Lead high-impact AI and ML initiatives with real-world business value
• Work on cutting-edge technologies including Generative AI and LLM-based systems
• Collaborate with skilled engineers, data scientists, and cloud experts
• Competitive compensation, continuous learning opportunities, and a strong growth-oriented culture