Job Description
Join the Future of Intelligence
Apex AI Solutions is at the forefront of the generative AI revolution, building scalable infrastructure that powers next-generation applications. We are seeking a visionary Senior Machine Learning Engineer to join our elite engineering team and help define our 2026 roadmap for large language model deployment and optimization.
In this role, you will not just maintain existing systems; you will architect the backbone of our AI ecosystem, ensuring our models are not only accurate but also responsible, efficient, and scalable.
Why You’ll Thrive Here:
- Impactful Work: Directly influence the architecture of AI systems used by millions.
- Innovation: Work with state-of-the-art technologies in a fast-paced, agile environment.
- Growth: Take on technical leadership responsibilities and mentor junior engineers.
Core Responsibilities:
- Design, develop, and deploy state-of-the-art machine learning models and NLP pipelines using Python and PyTorch/TensorFlow.
- Optimize model inference latency and throughput for high-volume production environments.
- Collaborate with product managers and data scientists to translate business requirements into technical solutions.
- Implement MLOps best practices, including CI/CD, automated testing, and monitoring.
- Drive the technical vision for the 2026 AI infrastructure, ensuring scalability and cost-efficiency.
- Mentor team members and conduct code reviews to maintain high engineering standards.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning, NLP, or deep learning engineering.
- Strong proficiency in Python, SQL, and at least one major deep learning framework (PyTorch, TensorFlow, or JAX).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Deep understanding of distributed systems, data structures, and algorithms.
- Demonstrated ability to mentor others and lead technical initiatives.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and NLP pipelines using Python and PyTorch/TensorFlow.
- Optimize model inference latency and throughput for high-volume production environments.
- Collaborate with product managers and data scientists to translate business requirements into technical solutions.
- Implement MLOps best practices, including CI/CD, automated testing, and monitoring.
- Drive the technical vision for the 2026 AI infrastructure, ensuring scalability and cost-efficiency.
- Mentor team members and conduct code reviews to maintain high engineering standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning, NLP, or deep learning engineering.
- Strong proficiency in Python, SQL, and at least one major deep learning framework (PyTorch, TensorFlow, or JAX).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Deep understanding of distributed systems, data structures, and algorithms.
- Demonstrated ability to mentor others and lead technical initiatives.