Artificial Intelligence Engineer

TekIT Software Solutions Pvt. Ltd. (India & USA)

6 years

0 Lacs

pune maharashtra india

Posted:1 day ago| Platform:

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Skills Required

ai ml design rest api reasoning planning model versioning monitoring authentication jwt oauth scalability research prototype cutting data coding numpy pytorch preprocessing training evaluation fastapi flask deployment aws gcp engineering retrieval debugging optimization

Work Mode

On-site

Job Type

Full Time

Job Description

AI Engineer

4–6 years of hands-on expertise

Key Responsibilities

Design, build, and deploy
AI/ML models
for classification, prediction, recommendation, and optimization.
Build and deploy
REST APIs
for ML/AI models using frameworks such as
Flask
or
FastAPI
.
Apply
asynchronous programming
and
high-performance API design
.
Work with
Generative AI frameworks
(LLMs, Diffusion models, Transformers, etc.) to develop next-gen AI solutions.
Build and orchestrate
Agentic AI systems
capable of reasoning, planning, and executing tasks autonomously.
Fine-tune and optimize
Large Language Models (LLMs)
for domain-specific use cases.
Manage
model versioning, monitoring, and scaling
for APIs in production environments.
Implement
API authentication and security
(JWT, OAuth, etc.).
Integrate AI models with
APIs, databases, and enterprise systems
for end-to-end workflows.
Evaluate model
performance, scalability, and reliability
, ensuring alignment with business goals.
Research, prototype, and productionize
cutting-edge AI techniques
.
Collaborate with
product managers, data scientists, and engineers
to deliver scalable AI-driven applications.

Required Skills & Experience

4–6 years
of hands-on experience in
AI/ML engineering
.
Strong coding skills in
Python
(NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
Expertise in
Generative AI
(LLMs like GPT, LLaMA, Claude, diffusion models, etc.).
Experience with
Agentic AI frameworks
(LangChain, LlamaIndex, AutoGPT, CrewAI, or similar).
Solid understanding of
NLP, embeddings, and vector databases
(Pinecone, Weaviate, FAISS, Milvus).
Strong knowledge of the
ML lifecycle
(data preprocessing, training, evaluation, deployment).
Expertise in building
REST APIs
with FastAPI/Flask and integrating them into applications.
Experience with
containerized solutions
using
Docker
&
Kubernetes
.
Deployment experience across
APIs, containers, and cloud platforms
(AWS/GCP/Azure).
Proficiency in
prompt engineering, RAG (Retrieval Augmented Generation)
, and
model fine-tuning
.
Strong
problem-solving, debugging, and optimization skills
.

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