Senior Software Engineer developing machine learning geospatial products for Planet. Collaborating with engineers and scientists on innovative remote sensing analytics.
About the role
- Own the long‑term architecture, roadmap, and execution for source discovery, acquisition optimization, and content understanding.
- Lead design reviews, set engineering standards, and drive cross‑team alignment with Product, Data, and Infra.
- Mentor and uplevel MLEs through technical direction, pairing, and reviews.
- Train/fine‑tune LLMs and NLP models for classification, extraction, and instruction‑following; design eval loops and guardrails.
- Design features and frameworks for sharing features across models.
- Productionize models for large-scale inference; drive latency, reliability, and cost efficiency (quantization, distillation, caching).
- Establish offline/online evaluation, gold sets, and automated regressions; run A/B and canary/shadow launches.
- Work with human and automated labeling sources to define data labeling standards.
- Partner on data strategy, labeling/weak supervision, and feedback loops to expand coverage and improve precision/recall.
- Define and meet SLOs for data quality, model performance, and serving reliability; lead incident playbooks and postmortems.
- Measure and drive downstream impact on revenue and engagement.
Requirements
- 5+ years building ML products end‑to‑end, including 2+ years as a tech lead driving multi‑quarter roadmaps and cross‑functional execution.
- Deep hands‑on experience with NLP/LLM training and inference (PyTorch, Python); strong grounding in evaluation, prompt/data design, and fine‑tuning.
- Proven track record shipping models at scale: feature/data pipelines, online serving, monitoring/observability, and cost/perf trade‑offs.
- Strong software engineering in Python with an eye for software engineering best practices.
- Experience mentoring senior engineers and influencing partner teams.
- Masters or PhD in ML related studies.
- LLM efficiency techniques (LoRA/adapters, distillation, quantization, prompt caching) and cost control strategies.
- MLOps at scale with tools like Airflow, Spark/Presto, Triton, vLLM.
Benefits
- This position is not eligible for relocation assistance
- Visit our PinFlex page to learn more about our working model.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
PA
PartSpaceMachine Learning Engineer – m/f/d
Machine Learning Engineer responsible for optimizing AI pipelines at Easy2Parts. Join a growing team to revolutionize component sourcing with AI technology.
NO
NokiaAI/ML Engineer
AI/ML Engineer developing and deploying machine learning solutions for Nokia's network optimization projects. Collaborating with cross - functional teams to enhance network planning capabilities.
Machine Learning Platform Engineer for Coinbase, building foundational components for ML at scale. Collaborating on fraud combat, personalizing user experiences, and blockchain analysis.
CO
Machine Learning Engineer focused on building sophisticated models to protect Coinbase users from fraud. Engaging in hands - on technical role with modern AI/ML methodologies.
Senior ML Platform Engineer developing and maintaining scalable ML infrastructure at GEICO. Focused on Large Language Models and collaborating with data science and engineering teams.
ZE
Staff ML Engineer developing GenAI infrastructure at Zendesk. Leading design and optimization of ML platforms while fostering technical excellence and collaboration.
Senior Deep Learning Engineer developing deep learning models for wireless communications. Working on next - gen signal processing and radio access technologies at NVIDIA's Vietnam R&D center.
Leading a team of ML Engineers to design and deploy AI - driven solutions at Welldoc. Overseeing critical ML projects while collaborating with international teams.
Senior ML Platform Engineer building and scaling machine learning infrastructure for AI applications. Responsible for LLM deployment, Kubernetes management, and mentoring engineering teams.