Lead AI Engineer at Fulcrum Digital is an agile and next-generation digital acce · Pune · 8 - 9 years · ₹35L - ₹38L / yr · Posted 19 Mar 2026
Lead AI Engineer
at Fulcrum Digital is an agile and next-generation digital acce
Job Description
About the Role
We are seeking an experienced and hands-on Lead AI Engineer with 8-9 years of experience in developing, fine-tuning, and deploying machine learning and deep learning models, including Generative AI systems. The ideal candidate will have strong expertise in classification, anomaly detection, and time-series modeling, along with deep experience in Transformer-based architectures and modern LLM ecosystems.
This role requires technical leadership, architectural decision-making, and mentoring of AI engineers, while actively contributing to building scalable AI solutions. Expertise in model optimization, quantization, and Retrieval-Augmented Generation (RAG) pipelines is highly desirable.
Responsibilities
- Lead the design, development, and deployment of ML and deep learning models for classification, anomaly detection, forecasting, and natural language understanding tasks.
- Architect and build scalable AI and Generative AI solutions, including RAG pipelines for document search, Q&A, summarization, and enterprise knowledge systems.
- Design, train, and fine-tune deep learning models including RNNs, GRUs, LSTMs, and Transformer architectures (e.g., BERT, T5, GPT).
- Drive the fine-tuning and adaptation of large language models (LLMs) using techniques such as Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA or QLoRA.
- Apply model optimization techniques such as quantization, pruning, and efficient inference strategies to improve latency and reduce compute and memory footprint in production systems.
- Define and implement evaluation frameworks, track model performance, monitor model drift, and drive continuous model improvement.
- Lead collaboration with data engineering, backend, platform, and DevOps teams to productionize AI solutions using scalable infrastructure and CI/CD pipelines.
- Provide technical mentorship and guidance to junior and mid-level AI engineers and contribute to best practices in ML engineering.
- Ensure clean, reproducible code, maintain experiment tracking, documentation, and version control of models and datasets.
- Stay up to date with the latest advancements in LLMs, Generative AI, and AI infrastructure, and help drive adoption of new technologies.
Required Skills & Qualifications
- 8-9 years of hands-on experience in machine learning, deep learning, or data science roles.
- Strong programming expertise in Python and ML/DL libraries such as scikit-learn, pandas, PyTorch, and TensorFlow.
- Deep understanding of machine learning algorithms, deep learning architectures, and sequence/NLP modeling techniques.
- Extensive experience with Transformer models and open-source LLM ecosystems (e.g., Hugging Face Transformers).
- Hands-on experience building Generative AI applications and RAG-based systems using frameworks such as LangChain or LlamaIndex.
- Experience with model optimization and quantization techniques (dynamic/static quantization, INT8, etc.) for efficient inference.
- Strong understanding of embeddings, vector databases, and retrieval systems (e.g., FAISS, Pinecone, Azure AI Search).
- Experience with model evaluation, monitoring, and performance optimization in production environments.
- Familiarity with containerization (Docker), experiment tracking (MLflow), and CI/CD pipelines.
- Proven ability to lead technical initiatives and mentor engineering teams.
Preferred Qualifications
- Experience fine-tuning LLMs using SFT, LoRA, or QLoRA on domain-specific datasets.
- Exposure to MLOps platforms such as SageMaker, Vertex AI, or Kubeflow.
- Experience with distributed data processing frameworks like Spark and workflow orchestration tools such as Airflow.
- Contributions to research papers, technical blogs, patents, or open-source projects in ML, NLP, or Generative AI.
- Experience designing enterprise-scale AI platforms or AI-powered products.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Kody Technolab Limited
AI/ML Lead (7+ Years Experience)
Location: Ahmedabad / Gandhinagar
Experience: 7+ Years
Employment Type: Full-Time
Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy
cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have
strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and
cloud-based AI deployments.
Key Responsibilities
• Design, develop, and deploy Machine Learning and Deep Learning models for classification,
regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
• Build and maintain end-to-end ML pipelines including data preprocessing, feature
engineering, model training, validation, evaluation, and deployment.
• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related
frameworks.
• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama,
Claude, and Stable Diffusion.
• Collaborate with product, engineering, and business teams to translate requirements into
scalable AI solutions.
• Optimize model performance, scalability, and reliability for production environments.
• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.
• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence,
Mathematics, or a related field.
• 7+ years of hands-on experience in AI/ML product development.
• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and
Hugging Face.
• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
• Strong understanding of the ML lifecycle including model training, tuning, deployment,
monitoring, and optimization.
• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
• Experience with AWS, Azure, or GCP cloud platforms.
• Strong problem-solving and analytical skills.Preferred Skills
• Fine-tuning and deployment of Large Language Models.
• Experience with RAG (Retrieval Augmented Generation) architectures.
• Contributions to open-source AI projects or research publications.
• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
Why Join Kody Technolab Limited?
Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,
and enterprise-scale applications while collaborating with a highly skilled technology team.
Visit the Website to know more about us.
Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution
Kody Robots | Robotics Company in India for Autonomous Robots
Flask
DjangoJob Title: Senior AI Engineer
Experience: 5–10 years in software engineering, with 3+ years in AI/ML engineering preferred
Employment Type: Full-time
Department: Artificial Intelligence / Engineering
Location: Bangalore
We are looking for a highly skilled Senior AI Engineer to design, develop, deploy, and scale intelligent AI-powered applications and solutions. The ideal candidate will have strong expertise in machine learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and production-grade software engineering.
The candidate will work closely with product managers, data scientists, software engineers, and business stakeholders to translate complex business requirements into scalable, reliable, secure, and cost-effective AI solutions.
Key Responsibilities
1. AI Solution Design and Development
- Design, develop, and deploy end-to-end AI and machine learning solutions.
- Build intelligent applications using LLMs, Generative AI, NLP, and deep learning techniques.
- Develop scalable AI architectures and reusable components for enterprise applications.
- Evaluate AI models and select appropriate approaches based on accuracy, latency, cost, and business requirements.
2. Generative AI and LLM Engineering
- Develop LLM-powered applications using models from providers such as OpenAI, Anthropic, Google, or open-source ecosystems.
- Design and implement RAG pipelines, document processing workflows, semantic search, and knowledge retrieval systems.
- Build AI agents and multi-step workflows using appropriate orchestration frameworks.
- Implement prompt engineering, structured outputs, tool calling, and context management.
- Optimize model performance through evaluation, fine-tuning where appropriate, and inference optimization.
3. Machine Learning and Data Engineering
- Develop and operationalize machine learning models for classification, prediction, recommendation, and other business use cases.
- Work with structured, unstructured, and multimodal data.
- Build data preprocessing, feature engineering, model training, and validation pipelines.
- Apply appropriate model evaluation techniques and statistical methods.
4. Production Deployment and MLOps / LLMOps
- Deploy AI solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Build automated CI/CD pipelines for AI applications and model deployment.
- Implement model versioning, experiment tracking, monitoring, and performance evaluation.
- Optimize inference latency, throughput, infrastructure utilization, and operating costs.
- Establish observability for AI applications, including token usage, retrieval quality, latency, failures, and model behavior.
5. Software Engineering and System Architecture
- Develop production-quality applications and APIs using Python and modern backend frameworks.
- Design RESTful APIs, asynchronous processing systems, and microservices where appropriate.
- Integrate AI services with enterprise applications, databases, and third-party systems.
- Use relational databases, vector databases, caching, and distributed systems effectively.
- Apply software engineering best practices, including testing, code reviews, documentation, and design patterns.
6. Security, Quality, and Responsible AI
- Implement safeguards against prompt injection, data leakage, insecure tool execution, and unauthorized access.
- Apply appropriate privacy, security, and compliance controls to AI systems.
- Evaluate hallucinations, bias, reliability, and failure modes.
- Design human-in-the-loop workflows and fallback mechanisms for critical use cases.
7. Technical Leadership and Collaboration
- Lead technical design discussions and mentor junior AI engineers.
- Define engineering standards, coding practices, and AI development guidelines.
- Collaborate with cross-functional teams to deliver measurable business outcomes.
- Conduct code reviews, evaluate emerging technologies, and recommend practical innovations.
- Communicate technical trade-offs and solution architecture to both technical and non-technical stakeholders.
Required Technical Skills
Programming and Backend Development
- Strong proficiency in Python.
- Experience with FastAPI, Flask, or Django.
- Knowledge of REST APIs, asynchronous programming, data structures, algorithms, and software design principles.
- Experience with Git, automated testing, and CI/CD.
AI and Machine Learning
- Strong understanding of supervised and unsupervised learning, model evaluation, and statistical concepts.
- Hands-on experience with PyTorch, TensorFlow, or scikit-learn.
- Knowledge of NLP, embeddings, transformers, and deep learning fundamentals.
Generative AI and LLMs
- Hands-on experience building production applications using LLM APIs or open-source models.
- Strong understanding of RAG architecture, embeddings, chunking, reranking, and retrieval evaluation.
- Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or pgvector.
- Familiarity with orchestration frameworks such as LangChain, LangChain, or comparable tools.
- Experience with tool calling, structured generation, agent workflows, and LLM evaluation.
Cloud and Infrastructure
- Experience with AWS, Azure, or Google Cloud.
- Working knowledge of Docker and Kubernetes.
- Familiarity with model serving, scalable APIs, monitoring, and production deployments.
- Experience with MLOps or LLMOps practices.
Databases and Data Processing
- Strong SQL skills and experience with relational databases.
- Familiarity with NoSQL databases, data pipelines, and distributed processing.
- Experience working with unstructured data, document ingestion, and retrieval systems.
Preferred Qualifications
- Experience with fine-tuning, quantization, or serving open-source LLMs.
- Experience with multimodal AI, including text, image, audio, or video.
- Knowledge of agent evaluation, workflow orchestration, and multi-agent systems.
- Experience with AI security, guardrails, governance, and responsible AI.
- Experience optimizing AI workloads for latency, scalability, and cost.
- Contributions to open-source AI projects, research, or technical publications.
Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- Equivalent practical experience and demonstrated engineering expertise may be considered.
Key Success Metrics
- Quality, accuracy, and reliability of deployed AI solutions.
- Production adoption and measurable business impact.
- Reduction in inference costs and response latency.
- RAG retrieval quality and reduction in unsupported or incorrect responses.
- System availability, scalability, and operational stability.
- Delivery timelines, code quality, and technical mentoring effectiveness.
Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have
strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-based AI deployments.
Key Responsibilities
• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
• Build and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, evaluation, and deployment.
• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related frameworks.
• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama, Claude, and Stable Diffusion.
• Collaborate with product, engineering, and business teams to translate requirements into scalable AI solutions.
• Optimize model performance, scalability, and reliability for production environments.
• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.
• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.
• 7+ years of hands-on experience in AI/ML product development.
• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and Hugging Face.
• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
• Strong understanding of the ML lifecycle including model training, tuning, deployment, monitoring, and optimization.
• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
• Experience with AWS, Azure, or GCP cloud platforms.
• Strong problem-solving and analytical skills.
Preferred Skills
• Fine-tuning and deployment of Large Language Models.
• Experience with RAG (Retrieval Augmented Generation) architectures.
• Contributions to open-source AI projects or research publications.
• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
Why Join Kody Technolab Limited?
Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,
and enterprise-scale applications while collaborating with a highly skilled technology team.
Visit the Website to know more about us.
Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution
Kody Robots | Robotics Company in India for Autonomous Robots
About the Role
We are looking for an AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have strong expertise in Computer Vision, Generative AI, RAG pipelines, Voice AI, and LLM-powered applications, with experience delivering scalable, production-ready solutions across enterprise, healthcare, or SaaS environments
Key Responsibilities
- Design, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.
- Build and optimize LLM-powered applications for real-world business use cases.
- Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
- Build Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.
- Create and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.
- Work with open-source LLMs for inference, fine-tuning, evaluation, and deployment.
- Implement model monitoring, evaluation, guardrails, and performance optimization.
- Collaborate with DevOps and cloud teams for scalable deployments.
- Optimize AI systems for latency, cost, scalability, and production performance.
- Integrate AI services through APIs and enterprise applications.
Required Skills & Experience
- 4+ years of experience in AI/ML engineering and production deployments.
- Strong experience in Python and AI/ML development.
- Hands-on experience with Generative AI and LLM applications.
- Strong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.
- Experience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.
- Familiarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.
- Experience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.
- Exposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.
- Experience building RAG pipelines using:
- Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus
- Embeddings and retrieval optimization
- Experience with Prompt Engineering techniques for LLM optimization.
- Experience with Open Source LLMs such as:
- Llama, Mistral, Falcon, Gemma, DeepSeek, Qwen
- Experience with Voice AI technologies:
- Speech-to-Text (Whisper, Deepgram, Google STT)
- Text-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)
- Conversational Voice Agents
- Experience using frameworks/tools:
- LangChain, LangGraph, LlamaIndex, Hugging Face
- Understanding of fine-tuning, model evaluation, inference optimization, and AI observability.
- Experience deploying applications using:
- Docker, Kubernetes, CI/CD
- AWS / Azure / GCP
Preferred Qualifications
- Experience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.
- Exposure to MLOps practices and model lifecycle management.
- Understanding of AI governance, security, and responsible AI practices.
- Experience integrating AI with APIs and production services.
Nice to Have
- Knowledge of agentic AI workflows and orchestration.
- Experience with monitoring and evaluation frameworks.
- Exposure to multimodal AI applications
Education Qualifications
- B.Tech / M.Tech in CSE / IT / AI&ML only from good college.
Hiring for AI Engineer
Exp: 5 - 8 yrs
Edu : BE/B.Tech/MCA
Work Location : Pune
Skill Set:
Total experience ranging from 5 - 8 years in software engineering/AI roles
Min 5 years strong programming experience in Python or Typescript is a MUST
Min 2.5 years hands-on experience in AI with LLMs, RAG pipelines, and AI frameworks
Experience with cloud platforms (AWS/Azure/GCP)
Machine Learning (ML)
Deep Learning
Python🚀 WE’RE HIRING | AI/ML GENERATIVE AI ENGINEER
📍 Location: Remote
💼 Experience: 5+ Years
🔄 Position: Contract – Extendable
🔹 ROLE HIGHLIGHTS
➤ Build and deploy AI/ML amp; Generative AI solutions
➤ Develop LLM, RAG, NLP, Recommendation amp; Predictive solutions
➤ Work on AI Agents, Chatbots, Computer Vision amp; Content Intelligence
➤ Build ML models using PyTorch, TensorFlow, Keras amp; Scikit-learn
➤ Develop RAG solutions using LangChain, LlamaIndex, FAISS/Milvus
➤ Integrate OpenAI, Azure OpenAI, AWS Bedrock, Vertex AI amp; Hugging Face
➤ Build scalable AI APIs using Python, FastAPI/Flask/Django
➤ Contribute to Private AI amp; Smart Agentic Systems
⚙️ MUST-HAVE SKILLS
◆ Python – 3+ years
◆ AI/ML – 5+ years
◆ Generative AI – 2+ years
◆ LLMs, RAG, Embeddings , Transformers
◆ ML/DL, NLP amp; Predictive Analytics
◆ Cloud AI Platforms – Azure / AWS / GCP
◆ AI/ML Deployment | MLOps
Interview Process - F2F Round at Pune Location
Data ScienceJob Description:
We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the
AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.
Machine Learning & LLM Capability:
End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn. Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.
Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.
Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.
Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.
Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.
Project Ownership & Execution
Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.
Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.
Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.
Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.
System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.
Performance Under Pressure
Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.
High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.
Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.
Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.
Proven expertise in Python, system design, and scalable AI/ML architecture.
Deep knowledge of NLP, Computer Vision, and Deep Learning models.
Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).
Machine Learning (ML)About the Role We are seeking a highly technical, hands-on Senior AI/ML Tech Lead to drive the design, development, and deployment of cutting-edge Generative AI applications. In this dual-impact role, you wi l act as a primary individual contributor architecting core AI engines while simultaneously leading a team of engineers through task alocation, code reviews, and technical mentorship. The ideal candidate bridges the gap between state-of-the-art AI research (LLMs, Agentic frameworks, Advanced RAG, OCR) and production-grade ful-stack engineering (Python, FastAPI, React).
Key Responsibilities
Technical Leadership & Team Management (40%)
● Technical Oversight: Lead a team of AI, backend, and ful-stack engineers; alocate tasks, establish sprint priorities, and ensure timely delivery.
● Code Quality & Reviews: Conduct rigorous code reviews to maintain high engineering standards, security, performance, and scalability across AI and fu l-stack codebases.
● Architecture & Governance: Design end-to-end system architectures for AI solutions, ensuring seamless integration between frontend interfaces, backend APIs, and AI models.
● Mentorship: Guide and upskil team members on modern software practices, LLM engineering, and agentic design patterns. Hands-On Engineering & Development (60%)
● Generative AI & Agentic Systems: Architect, build, and optimize LLM-powered applications, multi-agent workflows (e.g., CrewAI, AutoGen, LangGraph), and autonomous AI agents.
● RAG & OCR Pipelines: Design and deploy advanced RAG (Retrieval-Augmented Generation) architectures and document processing pipelines utilizing OCR techniques (e.g., LayoutLM, PaddleOCR, Tesseract, Vision LLMs) to extract structured data from unstructured sources.
● Backend Systems: Build robust, asynchronous, high-throughput microservices and RESTful APIs using Python and FastAPI.
● Frontend Integration: Colaborate on or build modern web interfaces using React (e.g., Control Towers, operations dashboards, interactive chat interfaces).
● MLOps & Vector DBs: Oversee model deployment, prompt engineering, fine-tuning, vector database integration (Pinecone, Qdrant, Chroma, PGVector), and cloud infrastructure setup (Azure/AWS).
Required Qualifications & Skills
● Overall Experience: 8 to 10 years of professional software engineering experience.
● AI/ML Domain Experience: 3 to 4+ years of dedicated, hands-on experience building and deploying AI/ML, OCR, and Generative AI solutions in production.
● Core Technical Stack: ○ Generative AI & LLMs: Extensive experience with commercial and open-source LLMs (OpenAI, Anthropic Claude, Llama), Agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), and LLM evaluation frameworks (LangSmith, TruLens, Ragas). ○ RAG & Unstructured Data: Strong knowledge of hybrid search, re-ranking, chunking strategies, vector databases, and document inte ligence workflows. ○ OCR & Vision Techniques: Hands-on experience with OCR engines (Tesseract, PaddleOCR, Azure Document Inteligence) and Multi-Modal/Vision LLMs for document extraction. ○ Backend: Deep expertise in Python and asynchronous frameworks (FastAPI, AsyncIO). ○ Frontend: Working proficiency in React (TypeScript/JavaScript) for building interactive web UI components. ○ Cloud & DevOps: Hands-on experience with cloud platforms (Azure / AWS), Docker, Kubernetes, and CI/CD pipelines.
Preferred / Good-to-Have Skills
● Experience with cloud-native data platforms (e.g., Microsoft Fabric, Snowflake, Azure SQL).
● Familiarity with cost optimization and latency reduction techniques for LLM inference (caching, semantic routing, model quantization).
● Prior experience in client-facing technical leadership or agile consulting environments.
What We Offer
● Opportunity to lead and build high-impact, state-of-the-art Generative AI systems.
● Colaborative engineering culture with room for technical ownership and direct business impact.
● Flexible work arrangements and competitive compensation package.
Amazon Web Services (AWS)PythonJob Summary
We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.
Key Responsibilities
- Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
- Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
- Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
- Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
- Integrate AI/ML models with enterprise applications and APIs.
- Fine-tune and evaluate ML/LLM models based on business requirements.
- Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
- Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
- Conduct model performance evaluation, optimization, and troubleshooting.
- Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
- Stay current with emerging AI/ML technologies, frameworks, and industry best practices.
Required Skills
- Strong programming experience in Python.
- Strong understanding of Machine Learning algorithms, statistics, and data structures.
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
- Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
- Experience with NLP, deep learning, or computer vision is an advantage.
- Experience developing and consuming REST APIs and microservices.
- Working knowledge of SQL and NoSQL databases.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of Docker, Kubernetes, CI/CD, and MLOps.
- Familiarity with Git and modern software development practices.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 4 years of relevant experience in AI/ML engineering or a related field.
- Experience building and deploying production-grade AI/ML solutions.
- Enterprise application development experience.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
- Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
- Experience with AI/ML model monitoring, evaluation, and optimization.
What You Bring
- Strong problem-solving and analytical skills.
- Ability to translate business requirements into practical AI/ML solutions.
- Strong software engineering and debugging capabilities.
- Ability to work independently as well as collaboratively in a cross-functional environment.
- Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Keywords
AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI
Location: Gurugram
Work mode: Hybrid
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Strong AI Engineer / Machine Learning Engineer profiles.
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Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
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Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
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Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
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Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
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Mandatory (Age) - Candidate's Age should be below 28 Years
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon