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Member of Technical Staff, Applied Machine Learning Engineer
Fireworks AI · San Mateo · New York
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What Fireworks AI asks for
From Fireworks AI's Member of Technical Staff, Applied Machine Learning Engineer ad, checked 6 Nov 2026.
Machine learning engineering
Practical experience with fine-tuning machine learning models using supervised fine-tuning or reinforcement learning from human feedback, plus a solid grasp of generative AI and enterprise infrastructure.
Customer technical leadership
At least 5 years of software engineering experience, preferably in customer-facing roles, with a history of leading complex technical projects and ensuring customer success.
PoCs and application deployment
Building and presenting technical demonstrations and proof of concepts, and designing end-to-end applications that use AI to solve specific user needs.
Python and performance optimization
Developing code in Python to improve the performance, scalability, and efficiency of machine learning models and internal platform features.
The ad asks for a bachelor's degree in computer science, engineering or a related field, and 5 or more years of software engineering experience. Based in San Mateo or New York.
How the example answers the ad
Three of the four requirements above, each matched to a line in the example.
Machine learning engineering
“Fine-tuned Llama-3 models on proprietary enterprise data, achieving a 25 percent improvement in domain-specific accuracy metrics.”
Fine tuning Llama 3 models on enterprise data shows machine learning engineering skill with generative AI models and supervised fine tuning techniques.
Customer technical leadership
“Mentored a team of 4 junior engineers on best practices for PyTorch development and production model monitoring.”
Leading 4 junior engineers in PyTorch development shows technical leadership. This experience at Meta contributes to the 5 years of software engineering required.
PoCs and application deployment
“Built a customer-facing AI demo framework that shortened the sales cycle by 20 percent through interactive prototype environments.”
Constructing an interactive prototype framework used for customer facing sales cycles shows the ability to build and present proof of concepts.
The whole example as text
Marcus Washington · Applied Machine Learning Engineer
Summary
Applied machine learning engineer with 6 years of experience in building scalable AI systems and production-grade inference pipelines. Orchestrates the full lifecycle of generative models from supervised fine-tuning to deployment in high-traffic enterprise environments. Optimizes model performance to reduce inference latency by 40 percent while maintaining accuracy across diverse datasets. Drives cross-functional collaboration by translating complex technical PoCs into impactful customer-facing solutions.
Experience
Applied Machine Learning Engineer · Meta
Menlo Park, CA · 2023 - Present
- Fine-tuned Llama-3 models on proprietary enterprise data, achieving a 25 percent improvement in domain-specific accuracy metrics.
- Optimized inference endpoints using TensorRT and vLLM to achieve 50ms latency for real-time customer support applications.
- Designed a distributed training pipeline that cut GPU resource consumption by 30 percent during large-scale experimentation.
- Deployed end-to-end AI applications that successfully supported 50,000 daily active users across global enterprise accounts.
- Mentored a team of 4 junior engineers on best practices for PyTorch development and production model monitoring.
Senior Machine Learning Engineer · Snowflake
San Mateo, CA · 2021 - 2023
- Built a customer-facing AI demo framework that shortened the sales cycle by 20 percent through interactive prototype environments.
- Automated supervised fine-tuning pipelines using Hugging Face Transformers, decreasing model iteration time by 45 percent.
- Reduced cold-start latency for inference services by 60 percent by implementing aggressive model quantization and caching strategies.
- Collaborated with product teams to define technical requirements for generative features integrated into the core data warehouse.
- Presented architecture reviews and technical roadmaps to senior stakeholders to secure funding for machine learning infrastructure expansion.
Software Engineer · Databricks
San Francisco, CA · 2020 - 2021
- Developed data ingestion pipelines in Python that processed 5TB of daily log traffic with zero data loss.
- Engineered internal monitoring tools that identified 99.9 percent of performance bottlenecks within the cloud platform.
- Contributed to the core library for distributed model evaluation, increasing team throughput for model benchmarking tasks.
- Optimized SQL query execution patterns which improved application response times for enterprise clients by 15 percent.
- Performed comprehensive performance profiling of asynchronous microservices to improve overall system stability and scalability.
Education
Master of Science in Computer Science · University of California, Berkeley
Berkeley, CA · 2018 - 2020
- Specialized in advanced deep learning and natural language processing coursework
- Completed thesis on efficient attention mechanisms for transformer architectures
- Graduated with honors and a 3.9 GPA
Bachelor of Science in Computer Science · Georgia Institute of Technology
Atlanta, GA · 2014 - 2018
- Focused studies on software engineering and distributed systems
- Achieved Dean's List status for 6 consecutive semesters
- Participated in the undergraduate research program for computer vision
Skills
Frequently asked questions
Is the example from an employee?
No. It is an AI-written example for this ad, made to show how a resume can answer it.
Do I need a master's degree to apply?
No. A bachelor's degree in computer science, engineering, or a related field is the minimum requirement. A master's degree is listed as a preferred qualification.
What kind of machine learning techniques should I know?
The role involves supervised fine-tuning and reinforcement learning from human feedback (RLHF or RFT). You should also have a solid understanding of generative AI and machine learning principles.
Where do I apply?
On the official Fireworks AI posting, through the job link on this page.
What happens when I tailor my resume here?
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