ML Software Engineer

I’m helping BIL Hire find a top candidate to join their team full-time for the role of ML Software Engineer.

You will scale generative AI infrastructure by building high-performance machine learning systems.

Compensation:

USD 150K - 265K/year

+ Commissions (:USD20K/year)

+ Bonuses (up to 5% of base compensation)

+ Bonuses (up to 10% of base compensation)

+ Overtime (USD30/hour)

Location:

California, MO, United States

Mission of BIL Hire:

"To empower businesses to scale seamlessly and professionals to advance meaningfully by delivering tailored, transparent, and efficient recruitment solutions."

What makes you a strong candidate:

• You are proficient in Testing, Swift, Software engineering, Python, Machine learning, Java.
• You have the potential to develop in Large language model (LLM), Generative artificial intelligence (Generative AI), Deep learning.
• English - Conversational

Responsibilities and more:

Requirements:

- Strong software engineering experience with proficiency in one or more programming languages such as C++, Python, Swift, or Java.

- Experience developing and deploying machine learning systems or applications in production environments.

- Knowledge of machine learning inference, model serving, or ML infrastructure.

- Experience with distributed systems, cloud infrastructure, or large-scale data-center environments.

- Understanding of generative AI, deep learning, or large language models is highly desirable.

- Strong problem-solving and analytical skills.

- Experience designing, building, testing, and maintaining reliable software systems.

- Ability to collaborate effectively with cross-functional engineering and machine-learning teams.

- Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related technical field, or equivalent practical experience.

Responsibilities:

- Design, develop, and maintain software systems supporting machine-learning inference workloads.

- Build high-performance ML applications and services running on Apple Silicon in data-center environments.

- Contribute to generative AI and Apple Intelligence initiatives.

- Develop scalable, reliable, and efficient production systems for advanced machine-learning workloads.

- Optimize software performance, reliability, and resource utilization.

- Collaborate with machine-learning engineers, software engineers, infrastructure teams, and other technical stakeholders.

- Participate in the full software development lifecycle, including design, implementation, testing, deployment, and maintenance.

- Troubleshoot complex technical issues and improve system performance and scalability.

- Help develop infrastructure and software supporting large-scale AI and machine-learning applications.

Your potential leader(s):

• Muhydeen Adebayo -