Expected Notice Period: 15 Days
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Remote
(*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, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for:
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
Keyskills: python natural language processing data engineering sql docker time series analysis software testing scikit-learn supervised learning forecasting airflow prophet data processing jupyter notebook machine learning asyncio devops ml ml pipelines
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