Fastino AI10.03.26
AI SCORE 8.5

Remote AI Engineer - LLM Development

$120K–$150K/year

About the Role

Join us as a Remote AI Engineer at Fastino, where we are building the next generation of large language models (LLMs). Our team, comprised of alumni from prestigious institutions like Google Research, Apple, Stanford, and Cambridge, is dedicated to developing specialized and efficient AI solutions. Fastino's GLiNER family of open-source models has been downloaded over 5 million times and is utilized by industry leaders such as NVIDIA, Meta, and Airbnb. With $25 million raised in our seed round, as highlighted in TechCrunch, we are backed by prominent investors including Microsoft and Khosla Ventures.

What You’ll Work On

  • Innovate by designing and deploying high-performance agentic systems that leverage Fastino’s optimized model architectures to outperform traditional LLM benchmarks.
  • Collaborate with engineering teams to bridge the gap between research and production, turning novel architectural breakthroughs into scalable, low-latency solutions for enterprise customers.
  • Drive rapid, iterative prototyping of AI functionalities, refining model performance and task accuracy based on real-world telemetry to ensure specialized models meet rigorous developer standards.
  • Own the stability and throughput of inference pipelines, proactively solving scalability bottlenecks to ensure models deliver consistent, reliable performance under massive operational loads.
  • Architect large-scale data and fine-tuning strategies to continuously improve the precision and domain-specific reliability of Fastino models.

Requirements

  • 2+ years of hands-on experience in AI/ML engineering roles.
  • Demonstrated proficiency with LLMs and a track record of applying AI/ML techniques to solve complex, unstructured problems.
  • Comfortable working across the stack from prompt engineering and vector DB tuning to Kubernetes deployment and API design.

Nice to Have

  • Experience building microservices that handle high-concurrency agentic workloads.
  • Familiarity with GLiNER or other information extraction architectures.

What We Offer

  • Competitive salary ranging from $120,000 to $150,000 annually.
  • Fully remote work environment, allowing you to work from anywhere in the world.
  • Opportunity to work with a talented team and contribute to cutting-edge AI technology.
  • Flexible working hours to promote work-life balance.
  • Access to professional development resources and training.
Why This Job8.5 of 10

This Remote AI Engineer position at Fastino offers a unique opportunity to work on cutting-edge LLM technology with a talented team. The competitive salary and fully remote work environment make it an attractive role.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficient in designing and implementing LLMs using frameworks such as TensorFlow or PyTorch, with a strong understanding of the underlying algorithms and architectures that drive these models.

Demonstrates self-discipline and proactive communication skills suited for remote work, effectively managing time and collaborating with cross-functional teams across different time zones.

Possesses a growth mindset and experience in deploying machine learning models in production using Kubernetes and microservices architecture, with an emphasis on API design for seamless integration.

Learning Resources

Deep Learning Specializationcourse

Career Path

Remote AI Engineer - LLM Development(Now)AI Engineer - Model Optimization(1-2 years)Lead AI Engineer - Product Development(3-5 years)

Market Overview

Market Size 2024
$126B
Annual Growth
38.2%
AI Adoption
70%
Investment
+150%
Labour Demand
+40%
Avg Salary
$130K

Skills & Requirements

Required
AIMachine LearningLLMs
Growing in Demand
Natural Language Processing (NLP)MLOpsCloud Computing (AWS, Azure)
Declining
Rule-Based SystemsTraditional Data Warehousing

Domain Trends

Rapid Growth of LLM Applications
The demand for Large Language Models (LLMs) is expected to increase by 50% annually as businesses integrate AI-driven solutions into customer service and content generation.
Shift Towards MLOps Practices
By 2025, 70% of AI projects will require MLOps practices for continuous integration and delivery, indicating a significant shift in how AI models are deployed and managed.
Increased Focus on Ethical AI
Over 60% of organizations are prioritizing ethical AI practices, leading to the development of frameworks that ensure transparency and fairness in AI applications.

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