Title - Lead AI Engineer
Client: Out Systems
Fulltime Position
Locations Menlo Park CA ( 3 days a week)
Were looking for an engineer who **builds the models** not just uses them. Someone who has trained neural networks from scratch constructed datasets that work and implemented papers before the libraries caught up. You understand AI deeply because youve debugged gradient flows at 2am and know why your loss function is misbehaving.
Lead AI Engineer** in the AI Research & Solutions group youll work hands-on at least 3 days a week in the office in Menlo Park leading the development of ML systems that power enterprise AI agents-systems that reason act and recover across long-horizon workflows. This is not a research scientist role. This is for the engineer who wrote the code that made the paper possible-the one who turned theory into working systems that ship. ---
### What Youll Do
**Build & Train Models** - Own the full pipeline: architecture design dataset engineering distributed training production deployment
Implement state-of-the-art techniques from papers-often before official implementations exist-translating math into working PyTorch code
Build experimentation infrastructure that enables rapid iteration on architectures training regimes and evaluation methods
**Build Agent Systems** - Create orchestration loops that enable AI to reason across multi-file changes invoke tools (compilers test runners debuggers) and recover from failures - Implement RL for code generation: execution-based rewards (RLVR) process supervision reward models and execution semantics alignment **Ship Production AI** -
Optimize for inference: quantization distillation pruning and serving infrastructure-understanding quality/latency/cost tradeoffs
Design evaluation pipelines that catch regressions and measure what matters; build guardrails and monitoring for production
Define integration architecture: APIs batching caching failure handling
**Lead Technically** - Mentor engineers on ML fundamentals debugging techniques and the craft of building reliable systems - Stay current with the field-read papers run experiments share findings separate signal from hype
## What You Bring #
**Required (5 years building AI that shipped)** - **Trained real models:**
Architecture design through deployment-not fine-tuning tutorials actual model development
**Deep ML fundamentals:** Backprop attention loss functions optimization-at a level where you can debug them
**Production engineering:** Expert Python PyTorch fluency distributed training GPU programming ML infrastructure at scale
**Dataset intuition:** Youve built datasets and can spot data issues from model behavior-you know data quality beats model size
**Agent architecture:** Built systems that plan act and adapt-agentic loops tool-calling multi-step reasoning pipelines
**Strong Signals** - Implemented papers from scratch before official code existed - Built or improved custom training infrastructure and experimentation pipelines - Worked on LLMs diffusion models or frontier architectures at a low level - Built RL training pipelines with non-standard rewards (execution-based verification process rewards) - Implemented code retrieval systems: RAG for code AST-aware search repository-level indexing - Worked on SWE-Bench or similar and understand what makes coding agents succeed or fail - Open-source ML contributions or published implementations
**Paths We Value** - Research backgrounds-PhDs open-source contributors or anyone who built models behind research - Non-traditional paths from physics math or quantitative fields; show us models youve trained not credentials
Best Regards
Ibraheem Mohammad
Momento USA Exceeding Customer Expectations
Email:
440 Benigno Blvd Unit#A 2nd Floor. Bellmawr NJ 08031
Interstate Business Park
Direct: / Desk: X 1019 / Fax:
Web:
Note: Momento USA is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex pregnancy sexual orientation gender identity national origin age protected veteran status or disability status.
Title - Lead AI Engineer Client: Out Systems Fulltime Position Locations Menlo Park CA ( 3 days a week) Were looking for an engineer who **builds the models** not just uses them. Someone who has trained neural networks from scratch constructed datasets that work and implemented papers before ...
Title - Lead AI Engineer
Client: Out Systems
Fulltime Position
Locations Menlo Park CA ( 3 days a week)
Were looking for an engineer who **builds the models** not just uses them. Someone who has trained neural networks from scratch constructed datasets that work and implemented papers before the libraries caught up. You understand AI deeply because youve debugged gradient flows at 2am and know why your loss function is misbehaving.
Lead AI Engineer** in the AI Research & Solutions group youll work hands-on at least 3 days a week in the office in Menlo Park leading the development of ML systems that power enterprise AI agents-systems that reason act and recover across long-horizon workflows. This is not a research scientist role. This is for the engineer who wrote the code that made the paper possible-the one who turned theory into working systems that ship. ---
### What Youll Do
**Build & Train Models** - Own the full pipeline: architecture design dataset engineering distributed training production deployment
Implement state-of-the-art techniques from papers-often before official implementations exist-translating math into working PyTorch code
Build experimentation infrastructure that enables rapid iteration on architectures training regimes and evaluation methods
**Build Agent Systems** - Create orchestration loops that enable AI to reason across multi-file changes invoke tools (compilers test runners debuggers) and recover from failures - Implement RL for code generation: execution-based rewards (RLVR) process supervision reward models and execution semantics alignment **Ship Production AI** -
Optimize for inference: quantization distillation pruning and serving infrastructure-understanding quality/latency/cost tradeoffs
Design evaluation pipelines that catch regressions and measure what matters; build guardrails and monitoring for production
Define integration architecture: APIs batching caching failure handling
**Lead Technically** - Mentor engineers on ML fundamentals debugging techniques and the craft of building reliable systems - Stay current with the field-read papers run experiments share findings separate signal from hype
## What You Bring #
**Required (5 years building AI that shipped)** - **Trained real models:**
Architecture design through deployment-not fine-tuning tutorials actual model development
**Deep ML fundamentals:** Backprop attention loss functions optimization-at a level where you can debug them
**Production engineering:** Expert Python PyTorch fluency distributed training GPU programming ML infrastructure at scale
**Dataset intuition:** Youve built datasets and can spot data issues from model behavior-you know data quality beats model size
**Agent architecture:** Built systems that plan act and adapt-agentic loops tool-calling multi-step reasoning pipelines
**Strong Signals** - Implemented papers from scratch before official code existed - Built or improved custom training infrastructure and experimentation pipelines - Worked on LLMs diffusion models or frontier architectures at a low level - Built RL training pipelines with non-standard rewards (execution-based verification process rewards) - Implemented code retrieval systems: RAG for code AST-aware search repository-level indexing - Worked on SWE-Bench or similar and understand what makes coding agents succeed or fail - Open-source ML contributions or published implementations
**Paths We Value** - Research backgrounds-PhDs open-source contributors or anyone who built models behind research - Non-traditional paths from physics math or quantitative fields; show us models youve trained not credentials
Best Regards
Ibraheem Mohammad
Momento USA Exceeding Customer Expectations
Email:
440 Benigno Blvd Unit#A 2nd Floor. Bellmawr NJ 08031
Interstate Business Park
Direct: / Desk: X 1019 / Fax:
Web:
Note: Momento USA is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex pregnancy sexual orientation gender identity national origin age protected veteran status or disability status.
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