Machine Learning Engineer (202510-J1000001)

Jeeno Tech; Coimbatore District; Hybrid; INR 800,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Performance-based bonus

Flexible hybrid/remote work options

Collaborative environment

Job summary

Jeeno Technologies Inc is seeking a Machine Learning Engineer in Coimbatore, India. The role involves designing and deploying scalable machine learning models while collaborating with data scientists and engineers to meet business needs. Candidates should have strong technical skills in Python, SQL, and machine learning libraries, along with a relevant degree.

We offer a competitive salary, performance-based bonuses, and flexible hybrid/remote work options in a collaborative environment where innovative ideas can take shape.

Qualifications

• 3–5 years of experience in applied machine learning or AI engineering.
• Proficiency in Python and ML libraries.
• Strong SQL and data wrangling skills.

Responsibilities

• Build, train, and optimize machine learning models for real-world applications.
• Clean, preprocess, and feature engineer large datasets for ML pipelines.
• Package models into APIs or services and deploy them into production environments.

Skills

Python

SQL

Machine Learning Libraries (scikit-learn, TensorFlow, PyTorch)

MLOps

Problem-solving skills

Communication skills

Education

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

Tools

Docker

Kubernetes

AWS SageMaker

GCP Vertex AI

Azure ML

Job description

You are applying for this Vacancy ID : 202510-J1000001

Position Title:

Machine Learning Engineer

Number of Positions:

1

Experience:

5+ Years

Location:

Coimbatore, India

Employment Type:

Full-Time

About the Role:

We are seeking a Machine Learning Engineer (Mid-Level) to design, build, and deploy scalable machine learning solutions. You will collaborate with data scientists, software engineers, and product teams to translate business needs into production-ready models. This is an exciting opportunity for someone with solid ML experience who wants to work end-to-end across data, modeling, and deployment.

Key Responsibilities

Model Development: Build, train, and optimize machine learning models for real-world applications (classification, regression, NLP, recommendation, forecasting, etc.).

Data Engineering: Work with large structured and unstructured datasets; clean, preprocess, and feature engineer for ML pipelines.

Deployment & Scaling: Package models into APIs or services, and deploy them into cloud or on-prem production environments.

MLOps: Implement monitoring, retraining, and performance tuning to ensure reliability of deployed models.

Collaboration: Work closely with data scientists (research focus) and software engineers (production systems) to bridge experimentation and deployment.

Documentation: Maintain clear documentation of data sources, model design decisions, and deployment processes.

Continuous Learning: Stay up to date with the latest ML frameworks, tools, and best practices.

Qualifications

Required

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
• 3–5 years of experience in applied machine learning or AI engineering.
• Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.).
• Strong SQL and data wrangling skills.
• Experience deploying ML models in production (e.g., REST APIs, Docker, Kubernetes, or cloud ML services such as AWS SageMaker, GCP Vertex AI, Azure ML).
• Knowledge of software engineering practices (Git, CI/CD, testing).
• Strong problem-solving and communication skills.

Preferred

• Experience with NLP, computer vision, or time series modeling.
• Familiarity with MLOps frameworks (MLflow, Kubeflow, Airflow).
• Experience in insert healthcare, retail or pharmaceutical industry.

What We Offer

• Competitive salary and performance-based bonus.
• Flexible hybrid/remote work options.
• A collaborative, innovative environment where you can have real impact.