Machine Learning Engineer (Remote)

Experience

Salary

Expected Notice Period

Shift

Opportunity Type

Placement Type

(*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.)What do you need for this opportunity?Must have skills required:async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQLA fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for:

Full-time Team: Data & ML Engineering

(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
  

How to apply for this opportunity?

• Step 1: Click On Apply! And Register or Login on our portal.
• Step 2: Complete the Screening Form & Upload updated Resume
• Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
  

About Uplers: