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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer

Nebula Innovations
San Francisco
Salary Estimate
USD 150.000 – USD 220.000
Live Update
31 Mei 2026
Deadline
31 Mei 2027

Job Description

We are seeking a visionary Senior Machine Learning Engineer to lead our AI research initiatives in San Francisco. Nebula Innovations is at the forefront of applying deep learning to solve real-world problems in healthcare and finance. You will be responsible for architecting scalable machine learning systems that drive our core product offerings.


As a key member of our technical team, you will bridge the gap between research and production, ensuring our models are not only accurate but also deployable in high-traffic environments. If you are passionate about pushing the boundaries of artificial intelligence and want to work with a world-class team, we want to hear from you.

Responsibilities

  • Design and Development: Architect and implement robust machine learning models and algorithms using Python, PyTorch, and TensorFlow.
  • Production Deployment: Oversee the end-to-end deployment of ML models into cloud environments (AWS/GCP) with a focus on scalability and low latency.
  • Data Pipeline Management: Build and optimize data pipelines to ensure high-quality, real-time data ingestion and processing.
  • Research & Innovation: Conduct cutting-edge research to stay ahead of industry trends and apply novel techniques to existing problems.
  • Collaboration: Work closely with cross-functional teams including data scientists, software engineers, and product managers to define technical requirements.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.

Qualifications

  • Education: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related technical field.
  • Experience: Minimum of 5 years of professional experience in machine learning, deep learning, or natural language processing.
  • Technical Skills: Proficiency in Python, C++, and SQL. Strong understanding of distributed systems and cloud computing architectures.
  • Tools: Experience with version control (Git), containerization (Docker), and orchestration (Kubernetes).
  • Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning Deep Learning TensorFlow PyTorch SQL AWS GCP Docker Kubernetes Data Engineering

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