Applied Machine Learning Engineer, Fireworks AI
EMEA
Generative AI platform enabling rapid scaling for developers and businesses
Be an early applicant
Generative AI platform enabling rapid scaling for developers and businesses
101-200 employees
Be an early applicant
101-200 employees
Company mission
To help every organization unleash the full power of artificial intelligence.
Role
Who you are
- 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
Desirable
- 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
What the job involves
- 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
- 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
Salary benchmarks
Our take
Whilst the development of generative AI is thought to be the reserve of large companies like Open AI, smaller startups such as Firework AI are making this technology easier to access and develop for smaller companies wanting to handle specific business needs using AI. As an open-source model API, it has one of the largest user bases - with over 12,000 users leveraging Fireworks AI’s software.
Though lacking the brand name recognition of generative AI developers like Google and Meta, Fireworks AI differentiates itself in a market crowded with large competitors through its unique approach to deploying its software. It creates smaller, production-grade, customizable generative AI models that can be launched privately and securely, rather than the non-private and inflexible models built by larger companies.
After its 2025 Series C round of $250M, Fireworks AI has been valued at over $4B, an impressive sum for a David in a sea of Goliaths. The company plans to use its funding to reshape AI infrastructure as well as expand globally. It will be interesting to see how the company evolves with its potentially disruptive business approach to generative AI.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Oct 2025
$230m
SERIES C
Jul 2024
$52m
SERIES B
Total funding: $307m
Company HQ
Redwood City, CA
Leadership
Lin Qiao
(Co-Founder & CEO)Previously a Senior Director of Engineering at Meta, a Tech Lead at Linkedin, a Research Staff Member at IBM Almaden Research Center and an Advisory Software Engineer at IBM Silicon Valley Lab.
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