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How We Work: Core Principles at ASAPP
At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship.
We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey.
We're actively looking for a highly experienced Senior Staff AI Engineer to join our team. You will play a pivotal role in designing, building, and deploying cutting-edge AI systems that power mission-critical enterprise applications. This role is ideal for an individual who thrives in ambiguity, is deeply technical, and has a strong product sense paired with deep expertise in foundational models and enterprise AI systems.
We're looking for someone with a passion for solving hard, real-world problems using modern machine learning techniques, especially large language models, RAG systems, and prompt engineering. You will lead end-to-end AI initiatives, from quick prototyping through to robust production deployments, while collaborating across engineering, research, and product teams.
What you'll do
- Drive the design and implementation of scalable ML/AI systems with a focus on large language models, vector databases, and retrieval-based architectures
- Leverage foundation models from major providers (OpenAI, AWS Bedrock, Anthropic, etc.) for both prototyping and production use
- Fine-tune, adapt, and evaluate LLMs for domain-specific enterprise applications
- Develop robust infrastructure for experimentation, training, deployment, and monitoring of AI models in production environments
- Optimize model performance and inference workflows for latency, cost, and accuracy
- Provide hands-on leadership and mentorship to other engineers, helping them grow technically and operationally
- Translate research ideas and early-stage prototypes into enterprise-grade ML systems
- Actively stay abreast of advancements in AI, open-source models, and MLOps best practices
- Establish and improve internal processes for experimentation, evaluation, and deployment of ML models
- Collaborate with cross-functional stakeholders to define AI roadmap and influence product direction
Required Qualifications
- 8+ years of professional experience in Machine Learning, with 3+ years focused on LLMs or NLP at scale
- Proficiency on Python and ML frameworks like PyTorch or TensorFlow
- Proven experience working with foundational models (OpenAI, Bedrock, Anthropic, HuggingFace)
- Hands-on experience with fine-tuning LLMs
- Strong understanding of RAG pipelines, prompt engineering, and vector search
- Experience building AI systems using vector databases
- Deep experience with Python and cloud services. AWS is required; experience with GCP, Azure, or Snowflake is a plus
- Experience deploying and scaling AI systems using Docker, Kubernetes, and CI/CD practices
- Demonstrated ability to move fast: prototype, test, and iterate quickly
- Strong written and verbal communication skills; ability to communicate complex technical ideas to both technical and non-technical audiences
- Comfortable with ambiguity and proactive in identifying and solving high-impact problems
- Highly organized, with the ability to manage multiple priorities and projects in parallel
Nice to Have
- Prior experience in MLOps, experimentation platforms, or model evaluation pipelines
- Contributions to open-source AI/ML tools
- Knowledge of additional languages such as SQL, Go, JavaScript, or TypeScript
- Graduate degree (MS or PhD) in Computer Science, Machine Learning, or related field
Benefits include:
Competitive compensation with stock options
Comprehensive medical, vision, and dental insurance401k matching
Fitness and wellness stipend
Mental well-being benefits
Professional learning and development stipend
Parental leave, including adoptive and foster parents
3 weeks paid time off (increases with tenure) along with sick leave, bereavement and jury duty
ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at [email protected] to obtain assistance. #LI-AG1 #LI-Hybrid #LI-Remote
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
