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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer

Quantum Leap Industries
San Francisco
Salary Estimate
USD 160.000 – USD 220.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Are you passionate about turning raw data into actionable intelligence? Quantum Leap Industries is seeking a world-class Senior Machine Learning Engineer to join our elite data science team in the heart of San Francisco.

We are on a mission to revolutionize the fintech landscape through predictive analytics and AI-driven decision making. As a key player in our R&D division, you will be responsible for developing scalable algorithms that drive our core product innovation. We offer a dynamic, high-performance environment where creativity meets rigor, and your code will have a tangible impact on millions of users.

Why Join Us?

  • Competitive compensation package and equity options.
  • Flexible remote-first work culture with a modern office in SF.
  • Access to cutting-edge cloud infrastructure and proprietary datasets.
  • Continuous learning budget and annual tech conferences.

Responsibilities

  • Design, develop, and deploy end-to-end machine learning pipelines using Python and PyTorch.
  • Collaborate with cross-functional teams of engineers, data scientists, and product managers to define data requirements and success metrics.
  • Implement robust A/B testing strategies to validate model performance and drive product optimization.
  • Conduct deep data analysis to uncover trends, anomalies, and opportunities for business growth.
  • Mentor junior data scientists and conduct code reviews to maintain high engineering standards.
  • Optimize algorithms for low latency and high throughput in production environments.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Proven experience with large-scale data processing frameworks (Spark, Hadoop, or Kafka).
  • Strong proficiency in SQL, Python (Pandas, NumPy, Scikit-learn), and experience with R or Julia.
  • Experience deploying and serving machine learning models via Docker, Kubernetes, or AWS SageMaker.
  • Excellent problem-solving skills with a focus on data-driven decision making.
  • Strong communication skills with the ability to translate complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning PyTorch TensorFlow SQL Spark Docker AWS A/B Testing Data Engineering

Ready to Take on This Challenge?

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