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Temporal Software Engineer Jobs in Michigan (NOW HIRING)

Develop robust metrics and evaluation frameworks for lane and route network accuracy, temporal ... Strong programming skills in Python and/or C++ with experience in modular software design and ...

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... with software developers/ engineers and architects to provide consultative guidance and direction ... NET developer/ C# development background. * Experience with Confluent Kafka and Temporal is ...

... software development. Our data science engineers employ statistical modelling and measurement ... Experience with temporal data and/or robotics sensor data WHAT WE OFFER * We are committed to ...

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Temporal Software Engineer information

What is a Temporal Software Engineer?

A Temporal Software Engineer is a developer who specializes in building, maintaining, and optimizing applications using the Temporal open-source workflow orchestration platform. Temporal enables engineers to manage complex, long-running, and distributed workflows in a reliable and scalable way. Temporal Software Engineers typically design workflows, implement fault-tolerant logic, and help teams automate business processes that require reliability and durability. Their expertise ensures that workflows can recover from failures, maintain state, and handle retries without losing data or process integrity.

What are the key skills and qualifications needed to thrive as a Temporal Software Engineer, and why are they important?

To thrive as a Temporal Software Engineer, you need strong software engineering fundamentals, proficiency in distributed systems concepts, and experience with languages like Go, Java, or TypeScript. Familiarity with Temporal's workflow orchestration platform, cloud infrastructure tools, and CI/CD systems is typically expected. Excellent problem-solving, collaboration, and communication skills help in designing resilient workflows and working with cross-functional teams. These skills are crucial for building reliable, scalable solutions that leverage Temporal for complex business processes.

What are some common challenges faced by Temporal Software Engineers when designing workflows, and how can they be addressed?

Temporal Software Engineers often encounter challenges such as managing complex workflow dependencies, handling failure recovery, and ensuring workflow scalability. These challenges can be addressed by leveraging Temporal’s robust retry mechanisms, designing idempotent activities, and breaking workflows into smaller, reusable components. Collaboration with DevOps and QA teams is also crucial to ensure workflows are resilient and thoroughly tested in distributed environments.

What is the difference between Temporal Software Engineer vs Cloud Software Engineer?

AspectTemporal Software EngineerCloud Software Engineer
Required CredentialsBachelor's in CS or related, experience with Temporal SDKsBachelor's in CS or related, cloud platform certifications (AWS, Azure)
Work EnvironmentDeveloping distributed, event-driven applications using TemporalDesigning and deploying cloud-based solutions across platforms
Industry UsageTech companies implementing workflow orchestrationBroad industry use, including SaaS, enterprise, and startups
Search & Comparison IntentFocus on Temporal-specific skills and workflowsBroader cloud infrastructure and deployment skills

In summary, a Temporal Software Engineer specializes in building and maintaining workflow orchestration using Temporal, while a Cloud Software Engineer works on deploying and managing cloud-based applications across various platforms. Both roles require strong programming skills, but their focus areas differ significantly.

How much does a Temporal Software Engineer make?

A Temporal Software Engineer's salary typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Skilled engineers with expertise in distributed systems and workflow orchestration tools like Temporal are often compensated at the higher end of this range.

What job categories do people searching Temporal Software Engineer jobs in Michigan look for?

The top searched job categories for Temporal Software Engineer jobs in Michigan are:

What cities in Michigan are hiring for Temporal Software Engineer jobs?

Cities in Michigan with the most Temporal Software Engineer job openings:

Lead ML Engineer - Lane & Route Network Mapping

May Mobility

Ann Arbor, MI • On-site

$100K - $132K/yr

Full-time

Re-posted 25 days ago


Job description

Job Summary:
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. They are seeking a Lead ML Engineer to architect the next generation of their mapping and localization stack, focusing on developing advanced neural networks for lane and route network mapping.
Responsibilities:
• Lead the research, design, architecture, training and validation of advanced neural networks for vectorized mapping (e.g., MapTR), multi-camera BEV transformers, and multimodal fusion models to extract and model lane and route networks for both high-fidelity offline pipelines and real-time online mapping.
• Architect, design, and implement a production-grade lane and route network mapping stack, ensuring high-performance integration with upstream and downstream modules like Perception, Behavior, Policy, and Prediction.
• Drive major feature development from inception to deployment. This includes high-level architecture design, rigorous code reviews, automated testing, mentorship of junior engineers, and technical resolution.
• Own the end-to-end data strategy for the mapping domain, specifically focusing on lane and route networks. You will define data curation, auto-labeling, synthetic data, and active learning pipelines to capture and resolve long-tail scenarios.
• Develop robust metrics and evaluation frameworks for lane and route network accuracy, temporal consistency, and scaling across diverse Operational Design Domains (ODDs).
• Work independently with cross-functional teams to translate complex autonomy goals into clear software and system requirements.
• Collaborate with ML and Autonomy engineers to ensure the seamless deployment and validation of mapping features to the vehicle fleet.
• Stay at the research frontier by evaluating, adapting, and innovating cutting-edge techniques, including online vectorized HD map construction, end-to-end mapping models, and vision/fusion Foundation Models to deliver production-ready solutions.
Qualifications:
Required:
• Ph.D. or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong mathematical and engineering foundation.
• 7+ years of industry experience developing and deploying ML/DL models for mapping or computer vision at scale.
• Deep expertise in several of the following areas: Vectorized mapping networks (e.g., MapTR), BEV-based scene representation, and temporal modeling.
• Cross-modal calibration and fusion (e.g., Camera-to-LiDAR) within Bird's-Eye-View (BEV) unified representation spaces.
• Transformers or Graph Neural Networks (GNNs) applied to structured lane geometry and topological connectivity.
• Lane-level topology and connectivity, intersection modeling, and lane/road network graph construction.
• Computer Vision Foundations: Object detection, classification, segmentation, tracking, depth estimation, and 3D reconstruction.
• Strong understanding of HD maps, including lane and road network geometry modeling, connectivity, and semantic attributes.
• Expertise in ML/DL development using PyTorch or TensorFlow, including experience with distributed training, synthetic data generation, large-scale dataset handling, and data curation strategies.
• Strong programming skills in Python and/or C++ with experience in modular software design and Linux-based development.
• Proven leadership in guiding technical roadmaps, mentoring engineers, and driving measurable improvements in model performance and system reliability.
• Strong communication skills with the ability to lead technical discussions and align with cross-functional teams.
Preferred:
• 10+ years of experience in ML/DL for autonomous driving or ADAS systems.
• Experience with self-supervised and/or semi-supervised learning for large-scale representation learning.
• Experience utilizing Vision-Language Models (VLMs) and/or Foundation Models for auto-labeling and long-tail (edge-case) detection.
• Expertise in ML optimization for real-time products with limited compute, such as quantization, pruning, or distillation of large transformer models.
• A proven record of inventions and/or publication record at top-tier conferences (e.g., CVPR, NeurIPS, ICCV, ECCV, ICLR).
Company:
May Mobility is a manufacturing firm that designs and develops autonomous technology vehicles for self-driving transportation solutions. Founded in 2017, the company is headquartered in Ann Arbor, USA, with a team of 201-500 employees. The company is currently Growth Stage.