Machine Learning Engineer

Carrerlift; Bengaluru; On-site; INR 150,000 - 210,000; Full time

Job summary

Carrerlift is seeking an ML engineer to collaborate with product, engineering and customer teams to translate business problems into well-scoped ML challenges.

You will source, clean, and structure datasets, build models from classifiers to transformers, and deploy them with attention to latency, cost, and reliability at scale. You will design evaluation frameworks and feedback loops to drive continuous improvements.

Qualifications

• 2-5 years hands-on engineering experience with ML/AI systems in production.
• Strong Python fundamentals and ability to write clean, maintainable code.
• Experience with large language models, prompt engineering, API integrations, or simple pipelines.

Responsibilities

• Collaborate with product, engineering, and customer teams to frame ML problems.
• Source, clean, and structure datasets; build data pipelines when needed.
• Develop models from classifiers to transformers and LLMs; choose appropriate complexity.
• Move models from notebooks to production; optimize latency, cost, and reliability at scale.
• Design evaluation frameworks and feedback loops to drive continual performance improvements.

Skills

Python

ML in production

Prompt engineering

Debug production issues

Tools

APIs

Data pipelines

Cloud services

Job description

Batch: 2020/2021/2022/2023/2024.

About the role:

• Work closely with product, engineering, and customer-facing teams to understand business problems and translate them into well-scoped machine learning challenges
• Source, clean, and structure datasets needed to train and evaluate models, often building datasets from scratch when off-the-shelf options don't exist
• Build and train models across the full spectrum, from simple classifiers through neural networks, transformers, and small or large language models, selecting the appropriate complexity for each problem
• Move models from development notebooks into production environments, optimizing for latency, cost, and reliability at scale
• Design evaluation frameworks that measure what actually matters for the business, and build feedback loops to continuously improve model performance

What we're looking for:

• 2-5 years of hands-on engineering experience, with solid exposure to building or working with ML or AI systems in production environments
• Strong Python fundamentals and comfort writing clean, maintainable code; ability to debug production issues effectively
• Experience with large language models, including prompt engineering, API integrations, or building simple pipelines and agents
• Action-oriented mindset—you take initiative without needing detailed instructions, prioritize shipping over over-engineering, and own your work end-to-end
• Willingness to learn quickly in a fast-moving environment and the ability to ask thoughtful questions that move projects forward