๐ Position: Machine Learning Engineer
๐ Location: San Francisco, CA (Hybrid โ 3 days onsite/week)
Locals are highly preferred.
Must be authorized to work in the U.S. (No OPT/CPT).
Important Submission Guidelines (Please Read Before Applying)
To ensure the highest quality and integrity of applications,
we are only accepting genuine profiles with verifiable, hands-on experience
for this role.
- Must be available for
video screening with camera ON
(live coding or scenario-based questions may be included).
- Must have
solid, real-world Machine Learning experience
(not academic-only or training-only).
๐ Job Description:
We are seeking a highly skilled
Machine Learning Engineer
with strong programming capabilities and hands-on experience building, deploying, and operationalizing ML models. The ideal candidate will work closely with business stakeholders to design and deliver scalable ML solutions, especially within
Financial Services, Equity, or Fixed Income trading
domains.
โญ Key Responsibilities:
- Develop robust ML models using Python, Java, and other relevant programming languages
- Apply strong knowledge of ML algorithms, statistical techniques, and optimization methods
- Build end-to-end ML pipelines including data preprocessing, feature engineering, training, testing, deployment, and monitoring
- Work with ML frameworks such as TensorFlow, PyTorch, and scikit-learn
- Partner with data engineering and business teams to design scalable ML infrastructure and tooling
- Convert research prototypes into production-ready solutions
- Collaborate directly with business stakeholders, ensuring clear communication of insights and model outcomes
- Support ML solutions for Equity or Fixed Income trading use cases
๐ฏ Required Skills & Experience:
- Strong programming skills in
Python, Java
(additional languages a plus)
- Hands-on experience with
TensorFlow, PyTorch, scikit-learn
- Deep understanding of ML algorithms, data processing, and feature engineering
- Experience developing infrastructure for training, deploying, and monitoring ML models
- Ability to work independently and drive solutions end-to-end
