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AIML Engineer

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

Location

Chennai, Tamil Nadu, India

Salary

Not specified

Type

fulltime

Posted

Today

via linkedin

Job Description

Job Title:

Senior AI/ML Developer

Experience:

6\+ Years

Location:

Chennai

Job Type:

Full-Time

Job Summary

We are seeking a

Senior AI/ML Developer

with strong experience in building and deploying

scalable, production-grade machine learning systems

. The role involves designing end-to-end AI solutions, optimizing model performance, and implementing robust ML pipelines within a

cloud-native environment (AWS)

.

Key Responsibilities

  • Design and develop

end-to-end ML pipelines

(data ingestion → training → deployment → monitoring)

  • Build and deploy

scalable ML models and microservices

for production environments

  • Optimize

model inference performance

for real-time and high-throughput systems

  • Containerize and orchestrate ML workloads using

Docker and Kubernetes (EKS)

  • Collaborate with cross-functional teams to translate

business requirements into AI solutions

  • Implement

CI/CD pipelines and MLOps practices

(model versioning, monitoring, retraining)

  • Develop reusable and maintainable code for

model serving and workflows

  • Monitor production models and troubleshoot

performance, scalability, and integration issues

  • Ensure solutions follow

security, reliability, and enterprise standards

Required Skills

  • 6\+ years of experience in

AI/ML development and software engineering

  • Strong expertise in

Python

and ML frameworks (Scikit-learn, TensorFlow, PyTorch)

  • Experience with

model deployment in production environments

  • Hands-on with

AWS (EKS, S3, EC2, Lambda, SageMaker, CloudWatch)

  • Strong knowledge of

Docker and Kubernetes

  • Experience in

ML microservices and REST API development

  • Understanding of

MLOps practices (CI/CD, monitoring, versioning)

  • Strong foundation in

data pipelines and distributed systems

Preferred Skills

  • Experience with

LLMs, Generative AI, or NLP

  • Knowledge of

vector databases, feature stores, or Spark

  • Exposure to

real-time streaming / event-driven architectures

  • Familiarity with

ML monitoring and observability tools

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