Machine Learning Engineer

Position: Machine Learning Engineer

Location: Remote, US

About the Role:

• Develop and Manage AI/ML Infrastructure and Lifecycle: Build and maintain scalable and reliable AI/ML infrastructure to support model deployment, monitoring, and optimization. Contribute to the full AI/ML lifecycle—from development to production—while implementing observability tools to collect data, ensuring models perform reliably and enabling data-driven improvements.  
• Design, Develop, and Deploy Models (especially LLMs): A part of your role will focus on integrating and deploying foundational generative AI models, such as LLMs, using techniques like retrieval-augmented generation (RAG). You may also develop additional models to complement and interact with these foundational models, with potential for fine-tuning based on specific use cases. This includes understanding requirements, designing solutions, collaborating with data engineers for necessary data, and deploying models into production. You will also be responsible for developing other models as needed to support evolving product requirements. 
• Collaborate within a Cross-Functional Team: Work closely with product managers, product developers, threat analysts, data scientists, and other engineers to understand the business requirements and translate them into ML solutions. 
• Keep Pace with Research: Keep up with the latest research in machine learning, large language models, and cyber security and find ways to implement new findings into our core technology. 

What You Have: 

• Most importantly, a passion for ensuring data quality, observability, and model performance through effective monitoring, validation, and data collection practices. 
• Masters/PhD (or Bachelor’s with equivalent experience) in computer science, statistics, mathematics, or related field, or equivalent work experience 
• 2+ years of experience in data science, machine learning, or data analytics 
• Proficient in one or more programming languages, such as Python, R, or Scala 
• Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Scikit-learn 
• Experience with cloud platforms and services, such as AWS, Azure, or GCP 

Bonus Points: 

• Experience training and fine-tuning large-scale foundational models, such as LLMs, or developing other production-grade language models, with a strong understanding of managing AI infrastructure and projects in a DevOps/MLOps setting. 
• Familiarity with security concepts, tools, and solutions, such as threat detection, vulnerability scanning, encryption, or authentication 

What We Offer: 

• Top-of-market competitive salary, bonus, and equity package 
• 100% employer paid, comprehensive health insurance including medical, dental, and vision for you and your family 
• Unlimited PTO, with your manager’s approval 
• Flexible work environment where you manage your work day 
• A remote-first environment, with occasional travel to collaborate with customers, your team, and teammates from across the company in person 
• Home office reimbursement 
• 14 weeks of fully-paid parental leave 

Salary Range: $165,000-$215,000. This represents the typical salary range for this position based on experience, skills, and other factors.

Andesite is an equal opportunity employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.

We encourage candidates from all backgrounds to apply, even if you don't feel like you're a perfect fit. If you're passionate about contributing to our mission, we'd love to hear from you!