Poseidon · 13 hours ago
Senior ML/AI Engineer
Palo Alto, CA
Full-time
Hybrid
Senior Level
6+ years expPoseidon is an a16z-backed startup building a platform that coordinates supply and demand for specialized AI training data. The role involves leading the development of ML capabilities from prototypes to customer-facing products, focusing on building production-quality model and data systems while mentoring other engineers.
Computer Software
Hiring Manager
Johnny Newman
Responsibilities
Own end-to-end delivery of ML capabilities into product: define the technical plan, implement, productionize, and operate systems with clear quality, latency, and cost targets
Build and scale evaluation for voice AI and other modalities:
Design offline + online evaluation frameworks
Create workflows for quality measurement and continuous improvement
Partner with product to translate metrics into product requirements and SLAs
Lead fine-tuning and adaptation work:
Build and maintain pipelines for supervised fine-tuning and domain adaptation
Own dataset curation, training data strategy, and reproducibility
Engineer data and labeling systems that power learning loops:
Design schemas/manifests across modalities and automate validation
Build data quality checks: PII detection, deduplication, drift checks, consensus labeling, gold sets
Productionize model and pipeline infrastructure:
Refactor research prototypes into tested Python libraries, services, and batch jobs
Deploy and operate inference endpoints (real-time and batch)
Optimize for GPU/CPU cost and performance
Raise engineering standards and mentor:
Set best practices for testing, CI/CD, code review, documentation, and operational readiness
Mentor other engineers and help unblock cross-functional execution with researchers, PMs, and ops
Qualification
Required
6+ years of hands-on experience shipping ML systems to production (or equivalent depth via impactful projects)
Expert Python engineering skills, including writing maintainable libraries/services, tests, and performance-aware code
Strong experience with modern deep learning frameworks (PyTorch strongly preferred)
Proven track record owning production ML systems end-to-end, including: Data pipelines and training/evaluation workflows, Deployment (APIs, batch jobs, or streaming inference), Observability (metrics, logs, traces), on-call, and iterative reliability improvements
Experience with voice AI / speech (ASR, diarization, audio preprocessing, alignment, multi-speaker challenges)
Strong understanding of ML evaluation and measurement (dataset design, slice-based analysis, regressions, and statistical thinking)
Solid cloud infrastructure experience (AWS, GCP, or Azure), containerization (Docker), and production deployment patterns. Kubernetes experience is a plus
Excellent communication: ability to write clear technical plans, make tradeoffs, and align stakeholders
Preferred
Experience with multimodal systems (text + audio + image/video) and building unified data/eval abstractions
Experience with distributed training, GPU performance tuning, and large-scale experimentation
Experience with workflow orchestration and distributed compute (Ray, Spark, Dask, Airflow, Flyte, Prefect)
Familiarity with privacy, security, and compliance concerns in ML systems (PII, rights management, auditability)
Company
Poseidon
Real-world data for physical AI
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase