Sr Machine Learning Engineer - Alldus : Job Details

This range is provided by Alldus. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$180,000.00/yr - $220,000.00/yr

Direct message the job poster from Alldus

Principal Recruitment Consultant | AI & Machine Learning | Co-organizer of the AI in Action Podcast

Senior Machine Learning Engineer

About the Company

We're a leading financial services startup revolutionizing a specific untapped vertical. We have incredible product market fit and backing. Our teams leverage cutting-edge ML and AI to build predictive models, automate workflows and unlock new revenue opportunities.

What You'll Do

• Design, implement and maintain end-to-end ML pipelines: data ingestion, feature engineering, model training, evaluation and deployment
• Develop and productionize quantitative models for pricing, risk forecasting, alpha generation and other finance-focused use cases
• Integrate and fine-tune large language models (LLMs) for document analysis, report generation and conversational interfaces
• Translate business needs into scalable, high-performance solutions
• Monitor model performance in production, troubleshoot issues and iterate to improve accuracy, latency and robustness

What You Bring

• 5+ years of hands-on experience in applied science / ML engineering, with a track record of shipping production models in finance, fintech, or insurance tech.
• Strong proficiency in Python, ML libraries (scikit-learn, PyTorch, TensorFlow) and MLOps tools (Docker, Kubernetes, Airflow, MLflow, etc.)
• Demonstrated experience building predictive models for financial time series, credit/risk scoring or algorithmic strategies
• Practical expertise with LLMs: prompt engineering, fine-tuning and deployment (e.g., Hugging Face Transformers, OpenAI API)
• Solid software engineering skills: clean code, testing, CI/CD and version control
• Self-starter who can own projects end-to-end, from ideation and prototyping through to deployment and maintenance
• Excellent communication skills and ability to work cross-functionally in a fast-paced environment
• Experience at (or a very strong desire to join) an early-stage startup

Nice to Have

• Master's or PhD in CS, Statistics, Applied Math, Financial Engineering or related field
• Experience with cloud platforms (AWS, GCP or Azure) and distributed computing
• Background in algo-trading, portfolio optimization or high-frequency data analysis

If you're passionate about applying ML at scale in finance and thrive working independently on end-to-end solutions, we'd love to hear from you. Please apply with your resume and a brief note on your most relevant project.

Seniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionEngineering and Science

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