Time since we first saw it
Day 83
Up longer than most. Similar jobs usually come down between day 6 and day 71.
From 4,610 similar postings that came down. Coming down is not always a hire.
Data Scientist
Reads like a ML Engineer role: putting models into production.
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDevelop, evaluate, and deploy ML, deep learning and LLM models
Own the end-to-end data science lifecycle, from problem definition to monitoring
Build reproducible, well-documented model workflows and pipelines
Implement model QA/QC with validation, drift detection, and experiment logs
Collaborate with product and domain teams to shape modeling strategies
From the employer’s posting
Develop, evaluate, and deploy ML, deep learning & LLM models
Own end-to-end DS lifecycle: problem definition → deployment → monitoring
Build reproducible, well-documented model workflows & pipelines
Implement strong model QA/QC: validation, drift detection, experiment logs
Collaborate with product & domain teams to shape modeling strategies
Tools in this posting
- Python
- MLflow
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Source — Tool mentions in context
Data Scientist (3-6 years of experience - Remote/Hybrid Bengaluru) Design, build, and deploy ML and LLM-based systems that drive personalization, assist teachers, and improve programs. What you’ll do Develop, evaluate, and deploy ML, deep learning & LLM models Own end-to-end DS lifecycle: problem definition → deployment → monitoring Build reproducible, well-documented model workflows & pipelines Implement strong model QA/QC: validation, drift detection, experiment logs Collaborate with product & domain teams to shape modeling strategies Continuously improve performance, documentation, reliability & processes What we’re looking for 3–6 years in applied ML / ML engineering / NLP / LLM development Strong fundamentals: statistics, ML algorithms, deep learning Python (pandas, numpy, scikit-learn, PyTorch/TensorFlow) ML workflow tools (MLflow, experiment tracking, registries) Experience with LLMs, fine-tuning, embeddings, vector stores, RAG Experience deploying models through APIs or containerized workflows Key Success Factors High ownership, clean engineering, excellent documentation Excellent communication and collaboration across teams to translate needs into solutions Curiosity, fundamentals, and bias for shipping reliable systems
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 14, 202683 days ago
- Recorded sightings
- 122
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Rocket Learning is hiring
2 open jobs
Hiring recordYour next step
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Data Scientist (3-6 years of experience - Remote/Hybrid Bengaluru) Design, build, and deploy ML and LLM-based systems that drive personalization, assist teachers, and improve programs. What you’ll do Develop, evaluate, and deploy ML, deep learning & LLM models Own end-to-end DS lifecycle: problem definition → deployment → monitoring Build reproducible, well-documented model workflows & pipelines Implement strong model QA/QC: validation, drift detection, experiment logs Collaborate with product & domain teams to shape modeling strategies Continuously improve performance, documentation, reliability & processes What we’re looking for 3–6 years in applied ML / ML engineering / NLP / LLM development Strong fundamentals: statistics, ML algorithms, deep learning Python (pandas, numpy, scikit-learn, PyTorch/TensorFlow) ML workflow tools (MLflow, experiment tracking, registries) Experience with LLMs, fine-tuning, embeddings, vector stores, RAG Experience deploying models through APIs or containerized workflows Key Success Factors High ownership, clean engineering, excellent documentation Excellent communication and collaboration across teams to translate needs into solutions Curiosity, fundamentals, and bias for shipping reliable systems
Source details
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