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Senior Machine Learning Engineer (AI/ML)

Apex Innovations
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
5 Juli 2026
Deadline
5 Jul 2027

Job Description

Are you a visionary engineer ready to shape the future of Generative AI?

Apex Innovations is on a mission to redefine human-machine interaction through scalable, robust, and ethically sound Artificial Intelligence. We are seeking a Senior Machine Learning Engineer to join our elite AI division in San Francisco. You will be at the forefront of developing next-generation Large Language Models (LLMs) and multimodal systems.

In this role, you will not just write code; you will architect the infrastructure that powers intelligent applications used by millions. If you thrive in a fast-paced, high-impact environment and want to push the boundaries of what's possible in 2024 and beyond, we want to meet you.

Responsibilities

  • Design, develop, and deploy state-of-the-art machine learning models and algorithms.
  • Optimize and scale existing AI infrastructure for high-throughput, low-latency inference.
  • Collaborate with data scientists and product managers to translate business requirements into technical solutions.
  • Implement MLOps best practices to ensure model reliability, monitoring, and retraining pipelines.
  • Research and integrate cutting-edge advancements in Deep Learning and Natural Language Processing.
  • Conduct code reviews and mentor junior engineers to foster a culture of technical excellence.

Qualifications

  • 5+ years of professional experience in software engineering or machine learning.
  • Strong proficiency in Python, PyTorch, or TensorFlow.
  • Deep experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of deploying models to production environments.
  • Excellent understanding of statistical modeling and machine learning theory.
  • B.S., M.S., or Ph.D. in Computer Science, Mathematics, or a related field.

Required Skills

Python PyTorch TensorFlow AWS GCP Docker Kubernetes MLOps Machine Learning Deep Learning NLP SQL

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