Develop scalable data pipelines and automated workflows that transform raw sensor data and external map sources into reliable, high-quality maps for autonomous driving.
Responsibilities
Develop and maintain automated map production pipelines, covering data ingestion, alignment, map conflation, format conversion, validation, packaging, and release.
Build automated map validation tools to detect geometric inconsistencies, topology errors, connectivity issues, and missing or incorrect map attributes.
Develop scalable map storage and retrieval services, including map indexing, tile serving, lane-level queries, and APIs for autonomous driving applications.
Implement map format conversion and export tools, supporting industry-standard formats such as OpenDRIVE and Lanelet2 for simulation, planning, and evaluation.
Build robust data processing workflows for integrating vehicle sensor logs, HD maps, and third-party geospatial datasets.
Requirements
Bachelor's degree in Computer Science, Robotics, Software Engineering, or a related discipline
Master's degree in Computer Science, Robotics, Software Engineering, or a related discipline
Develop quantitative tools and Python applications supporting trading and research activities across Commodities (Agriculture, Metals, and Energy), focusing on pricing, backtesting, risk analysis, and PnL reporting.
Responsibilities
Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting
Build Python applications and data pipelines to explore, integrate and analyse alternative datasets, including weather and cargo data
Collaborate with Quantitative Researchers and Traders to translate trading ideas and business requirements into production applications and quantitative models
Architect, develop and maintain cloud applications in collaboration with infrastructure engineers, using AWS and related technologies
Develop and apply statistical and machine learning models to support research and trading across Agriculture, Metals, and Energy
Principal Software Engineer, Full Stack, building robust backend systems and APIs for a search-centric document analysis platform in global capital markets.
Lead AI & data science projects for government clients, building and deploying Python‑based data pipelines and ML models.
Compensation
A reasonable estimate of the current range is $110,700 to $184,500. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
Develop, test, and deploy data science and AI/ML solutions that support government mission objectives.
Build Python‑based data processing pipelines and workflows for raw and structured datasets.
Analyze data quality, model performance, and solution results to inform implementation decisions.
Collaborate with data engineers, technical teams, and client stakeholders to translate analytical needs into technical requirements.
Document methods, models, data sources, and results to support solution delivery and operational use.
Develop custom software solutions to design, code, and enhance components across systems or applications using modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with cross-functional teams to understand project requirements and translate them into effective software solutions.
Maintain and enhance existing software components to improve performance and reliability.
Lead research program management for pre‑training ML and data teams, coordinating cross‑team initiatives, building lightweight processes, and driving execution of complex research projects.
Compensation
Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
Responsibilities
Embed within pre‑training ML and Data teams
Drive end‑to‑end execution of complex, cross‑team research initiatives
Coordinate operational rhythm of pre‑training research
Equip research leadership to make decisions quickly
Build lightweight processes for research environments
The base compensation range for the role in any of those locations is $183,100 USD - $340,000 USD. For any eligible US locations, unless otherwise noted, the base compensation range for this role is $158,900 USD - $295,100 USD. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.
Responsibilities
Design and build scalable backend services and APIs for document analysis platform
Write maintainable, high-performance server-side code and data processing pipelines
Define clear, efficient API contracts and contribute to service architecture decisions
Design and craft compositional API primitives to expedite document insights productionization
Build and maintain integrations with third-party services and internal ML systems
Requirements
Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience)
Quantitative Developer - Commodities (Python)NewQube Research & Technologies · London, United Kingdom
Senior Data ScientistDeloitte · Tampa, US
Research Program Manager, Pre-trainingReflection · San Francisco, US