Pay: Salary not listed in the saved posting
Work setup: Remote stated — work setup source
This is a remote position. Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.
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Employment: Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting

Apply at Neuralgo

What you’ll bring

All qualifications

Core experience

Bachelor’s/Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
3-5 years of experience in generative AI or related fields.
Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance.
Familiarity with RAG and other techniques for building generative models.
Experience with cloud-based ecosystems, especially AWS ML/GenAI services.
Excellent communication and collaboration skills.

Qualification wording

Bachelor’s/Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

3-5 years of experience in generative AI or related fields.

Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance.

Familiarity with RAG and other techniques for building generative models.

Experience with cloud-based ecosystems, especially AWS ML/GenAI services.

Excellent communication and collaboration skills.

Tools in this posting

Python
AWS
Docker

Source

- Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance. - Strong programming skills in Python. - Familiarity with RAG and other techniques for building generative models.

- Extensive experience with Git, Docker and a good understanding of Linux for managing servers. - Experience with cloud-based ecosystems, especially AWS ML/GenAI services. - Exposure to ML/GenAI frameworks and tools.

- Familiarity with RAG and other techniques for building generative models. - Extensive experience with Git, Docker and a good understanding of Linux for managing servers. - Experience with cloud-based ecosystems, especially AWS ML/GenAI services.

Posting record

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Status in our records: Live
First seen by us: Jun 2, 2026 · 137d ago
Recorded sightings: 51
Last seen by us: Oct 15, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Job description

View original posting ↗

This is a remote position.

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.

Design and develop generative AI models using techniques like RAG, transformers, and other relevant approaches.
Fine-tune pre-trained LLMs for specific tasks and domains.
Conduct research on new techniques for improving the performance and capabilities of generative AI models.
Apply software engineering rigor and best practices to machine learning /Generative AI pipelines.
Evaluate and analyse the performance of ML/generative AI models.
Stay up to date on the latest advancements in generative AI research.
Facilitate the development and deployment of proof-of-concept Generative AI systems

Requirements

Bachelor’s/Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
3-5 years of experience in generative AI or related fields.
Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance.
Strong programming skills in Python.
Familiarity with RAG and other techniques for building generative models.
Extensive experience with Git, Docker and a good understanding of Linux for managing servers.
Experience with cloud-based ecosystems, especially AWS ML/GenAI services.
Exposure to ML/GenAI frameworks and tools.
Excellent communication and collaboration skills.
Ability to work independently and in a team-oriented environment.
Methodical and meticulous towards work and planning

Your next step

Have your CV and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the salary range before committing time to the process.

Complete your application on neuralgo.zohorecruit.in. The employer’s form will show what is required.

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Source details

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Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay: No pay amount identified in the saved description.
Location & working pattern: Location not supplied.
This is a remote position. Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at neuralgo.zohorecruit.in ↗Read the full description ↓

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Machine Learning Engineer