Applied Machine Learning Engineer

About Us:

At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.

The Role:

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.

Key Responsibilities:

• Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.


• Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.


• Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.


• Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.


• New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.


• Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.


• Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field.


• 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.


• Robust coding skills required, preferably with proficiency in Python.


• Demonstrated ability to lead and execute complex technical projects with a focus on customer success.


• Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.

Preferred Qualifications:

• Master’s degree in Computer Science, Engineering, or a related technical field.


• Experience working in a startup or fast-paced environment.


• Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).


• Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.

Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.

Base Pay Range (Plus Equity)

$170,000 - $240,000 USD

Why Fireworks AI?

• Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.


• Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.


• Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.


• Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.