Lead AI/ML Engineer

Hithonix Solutions Private Limited; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Competitive compensation

Continuous learning opportunities

Growth-oriented culture

Job summary

A progressive technology company in India is seeking an experienced Lead AI/ML Engineer to drive technical vision and architecture for AI and Machine Learning initiatives. The role requires building end-to-end AI/ML systems, mentoring teams, and employing cutting-edge technologies including Generative AI and LLMs. The ideal candidate has over 6 years of experience in AI with a strong background in Python and MLOps tools, alongside leadership capabilities to foster a collaborative culture and ensure timely delivery of solutions.

Qualifications

• 6+ years professional experience in AI, Machine Learning, or Deep Learning.
• 2+ years in a technical leadership or architect role.

Responsibilities

• Define and own end-to-end AI/ML system architecture including data pipelines and model training.
• Lead the complete ML lifecycle: problem definition, data analysis, feature engineering, model development.
• Mentor and guide AI/ML engineers and data scientists through code reviews.
• Encourage innovation in Generative AI, LLMs, and agent-based systems.

Skills

Python

ML/DL frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost

MLOps tools: MLflow, Kubeflow, Airflow

Docker

Kubernetes

SQL

Pandas

NumPy

NLP

Computer Vision

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Engineering, or related field

Tools

AWS (SageMaker)

Azure ML

GCP Vertex AI

Job description

Lead AI/ML Engineer – Hithonix Solutions Private Limited

Location: Whitefield, Bangalore
Employment Type: Full-Time (Onsite)
Experience Required: 6–7 Years

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 hands‑on leadership role will design scalable ML systems, lead end‑to‑end delivery of production‑grade AI solutions, and mentor a team of AI/ML engineers.

Key focus areas include building robust MLOps pipelines, deploying models at scale, and driving innovation in Generative AI, LLMs, RAG pipelines, and intelligent agents.

Key Roles & Responsibilities

• 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 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 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.

Leadership & Soft Skills

• 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.

Educational Qualifications

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

Why Join Hithonix Solutions?

• 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.

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