Senior Artificial Intelligence Engineer

Skillventory; Bengaluru; Hybrid; INR 1,500,000 - 3,000,000; Full time

Job summary

Skillventory in Bengaluru is seeking an experienced AI/ML engineer to deliver Generative AI models into production. You will design, train, and fine-tune advanced models, and collaborate with data scientists and engineers to deploy scalable solutions.

The role requires hands-on expertise with PyTorch/TensorFlow, NLP libraries, and cloud-based ML platforms, plus strong communication and leadership abilities to guide technical teams.

Qualifications

• Experience in AI/ML engineering with 5+ years delivering Generative AI models to production.
• Degrees in CS/Math/Stats or related field from top-tier institutions (IITs/NITs/BITs, etc.).
• Strong Python, SQL, and R programming with data science libraries such as NumPy and Pandas.
• Proven expertise with deep learning frameworks (PyTorch, TensorFlow, Keras) and NLP libraries.
• Experience with vector databases, LangChain, and embedding retrieval patterns; CI/CD for ML.

Skills

AI/ML engineering

Generative AI

Python

SQL

R

Mathematics

Statistics

Communication

Leadership

Problem solving

Education

Bachelor's degree in CS/Math/Stats or related

Master's degree

PhD

Tools

NumPy

Pandas

MatLab

scikit-learn

PyTorch

TensorFlow

Keras

MXNet

Caffe

Transformers

SparkNLP

Gensim

SpaCy

NLTK

Hugging Face

LangChain

LlamaIndex

Pinecone

FAISS

Weaviate

Milvus

AWS Sagemaker

GCP Vertex AI

Azure ML

Docker

Kubernetes

MLflow

Weights & Biases

LangSmith

CI/CD for ML

Job description

Required Skills :

• Experience in AI/ML engineering, with at least 5+ years delivering Generative AI models into production.
• Bachelors/Masters/PhD in Computer Science, Mathematics, Statistics, or related field from a top-tier institution IITs/NITs/BITs etc.
• Strong applied programming skills in Python, SQL, R and experience with data science libraries such as NumPy, Pandas, MatLab, scikit-learn.
• Proven experience with deep learning frameworks: PyTorch, TensorFlow, Keras, MXNet, Caffe.
• Familiarity with NLP and ML libraries: Transformers, SparkNLP, Gensim, SpaCy, NLTK, Hugging Face.
• Experience building and fine-tuning LLMs and integrating them with orchestration frameworks (LangChain, LlamaIndex).
• Expertise with vector databases (Pinecone, FAISS, Weaviate, Milvus) and knowledge of embedding retrieval patterns.
• Cloud-native ML experience (AWS Sagemaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes).
• Applied knowledge of classical ML algorithms (SVM, Decision Trees, Random Forests, regression, clustering) alongside modern DL/GenAI approaches.
• Strong knowledge of CI/CD for ML, model observability (MLflow, Weights & Biases, LangSmith), and governance frameworks.
• Excellent problem-solving skills, communication, and ability to lead technical teams.