Machine Learning Engineer

2 days ago

Hyderabad, Telangana, India Uplers Full time
Job Description

Must have skills required :

Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, Machine Learning, Python, SQL

Good to have skills :

async workflows, MLOps, Ray Tune, NLP

B2B SaaS platform (One of Uplers Clients) is Looking for:

Machine Learning Engineer (Remote) who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.

Role Overview Description

We are a fast-moving startup building AI-driven solutions to the financial planning workflow. Were looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product.

Job Description-

Full-time Team: Data & ML Engineering

Were looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus)

WHAT YOU WILL DO-

- Build and optimize machine learning models from regression to time-series forecasting
- Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker
- Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn
- Design and deploy LLM-powered features and workflows
- Collaborate closely with product managers to turn ideas into experiments and production-ready solutions
- Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform

BASIC SKILLS

- Proven ability to work creatively and analytically in a problem-solving environment
- Excellent communication (written and oral) and interpersonal skills
- Strong understanding of supervised learning and time-series modeling
- Experience deploying ML models and building automated training/inference pipelines
- Ability to work cross-functionally in a collaborative and fast-paced environment
- Comfortable wearing many hats and owning projects end-to-end
- Write clean, tested, and scalable Python and SQL code
- Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing.

ADVANCED SKILLS

- Familiarity with MLOps best practices
- Prior experience with LLM-based features or production-level NLP
- Experience with LLMs, vector stores, or prompt engineering
- Contributions to open-source ML or data tools

TECH STACK

- Languages: Python, SQL
- Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter
- Infra: Docker, Airflow, S3, asyncio, Pydantic

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