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Information Technology 🏒 Full Time ⭐️ Verified

Senior Machine Learning Engineer

Nexus Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

About Nexus Future Tech:

We are a pioneering force in the AI landscape, dedicated to building the intelligent systems of tomorrow. As we scale our infrastructure for the next decade, we are seeking a visionary Senior Machine Learning Engineer to lead our advanced modeling efforts. If you are passionate about pushing the boundaries of what is possible with Generative AI and predictive analytics, we want to hear from you.

Why Join Us?

  • Competitive salary and equity package.
  • Comprehensive health, dental, and vision insurance.
  • Unlimited PTO and flexible remote-first culture.
  • Access to cutting-edge hardware and cloud resources.

Responsibilities

  • Design, develop, and deploy scalable machine learning models and algorithms to solve complex business problems.
  • Lead the full lifecycle of ML projects, from data ingestion and preprocessing to model training, evaluation, and productionization.
  • Collaborate closely with cross-functional teams of data scientists, engineers, and product managers to define technical requirements and roadmap.
  • Optimize existing models for latency, throughput, and resource efficiency in high-traffic environments.
  • Mentor junior engineers and conduct code reviews to maintain high standards of quality and best practices.
  • Stay abreast of the latest advancements in Deep Learning, NLP, and MLOps to drive innovation within the team.

Qualifications

  • Master’s degree or PhD in Computer Science, Mathematics, Statistics, or a related field (or equivalent practical experience).
  • 5+ years of professional experience in machine learning, with a strong portfolio of deployed models.
  • Expert proficiency in Python and major ML frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong understanding of MLOps principles, CI/CD pipelines, and containerization technologies (Docker, Kubernetes).
  • Experience with cloud platforms (AWS, GCP, or Azure) and large-scale data processing (Spark, Hadoop, or SQL).
  • Demonstrated ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning MLOps Docker Kubernetes AWS SQL Data Science Natural Language Processing GenAI

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