MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100, the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the engineering talent to match.

We're looking for a Senior Software Engineer to own the constraint-solving engine behind our Scheduling Agent, one of the most strategic bets on our Planning & Scheduling roadmap. The engine is a Python service built on CP-SAT that takes work orders, technicians, and a mix of hard and soft constraints, and produces a feasible weekly schedule that enterprise maintenance teams can trust. Your focus will be evolving the solver to handle increasingly complex, real-world scheduling scenarios and exposing it as tools for GenAI agent workflows.

This is a high-ownership role. You'll have the space to shape the modeling approach, partner closely with product and design on what scheduler users actually need, and ship iteratively against feedback from real enterprise customers.

What you'll do

• Own and evolve the Python optimization service that powers the Scheduling Agent, modeling, solving, and iterating on the constraint formulation as new use cases emerge.
• Design and implement increasingly sophisticated scheduling capabilities: trade and crew constraints, irregular capacity patterns, production downtime windows, multi-site considerations, and reactive re-scheduling.
• Build and maintain API routes and tools that expose the solver to GenAI agent workflows (tool calling, structured input/output).
• Partner with PM and design to translate messy real-world scheduling problems into solver constraints, and push back when "optimal" isn't what users actually want.
• Iterate the solver with real users via design partnerships and pilot deployments. Take feedback from human schedulers seriously and reflect it back into the model.
• Contribute to the surrounding Python service: performance, observability, testing, and reliability of the optimization runtime.
• Help shape how scheduling intelligence integrates with the broader MaintainX product over time, including learning from execution data to improve solver inputs.

About you

• 5+ years of professional software engineering experience, with significant time spent on optimization, constraint programming, or operations research problems shipped to real users.
• Strong fluency with CP-SAT and at least one other optimization paradigm (MILP via Gurobi/CPLEX/HiGHS, metaheuristics, or similar). You've hit the limits of one approach and made informed choices about when to use which.
• Solid Python service engineering: APIs, async, testing, profiling, observability. You can own a production service end-to-end.
• Academic grounding in Operations Research, Industrial Engineering, Computer Science, or a related quantitative field, at minimum a strong undergraduate foundation; advanced degrees are common in this space but not required.
• Track record of iterating optimization systems with real users, you've felt what happens when a human rejects the "optimal" answer and you've redesigned the model in response.
• Product mindset and delivery orientation, you ship, you measure, you iterate. You think about the user outcome, not just the objective function.
• Comfort with ambiguity. You can co-design the constraint data model with the team rather than waiting for a clean spec.
• Familiarity with GenAI tooling (LLM tool calling, structured output, prompt design for constrained generation) is expected.

Nice to have

• Experience at a known, reputable product company shipping optimization or scheduling products at scale.
• Exposure to learning-augmented optimization, using historical execution data to estimate durations, priors, or constraint weights.
• Domain experience in scheduling, workforce management, field service, manufacturing, logistics, or similar resource-constrained planning problems.
• Tech-lead experience or interest in growing into a tech-lead role on this team.

What's in it for you

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A Work Culture where:
• You'll work alongside folks across the globe that reflect the MaintainX values: Smart Humble Optimists.
• We believe in meritocracy, where ideas and effort are publicly celebrated.

About us

Our mission is to deliver one platform for maintenance, repair & operations teams to keep the physical world running. We believe the greatest asset in any organization is the people. That's why we built an intuitive, mobile-first solution to help boost productivity and collaboration across teams and locations.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

#LI-Remote

MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.

We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.

Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.

As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.

What you’ll do:

• Design, develop and optimize machine learning models for fault detection and classification end-to-end e.g. data and training modeling choices to evaluation strategies and production constraints.
• Perform EDA on vibration, OT and time-series data to uncover insights and identify patterns indicative of faults or anomalies.
• Conduct experiments and evaluation of various algorithms on time-series modeling, signal processing, and statistical methods, to optimize model performance.
• Partner with PMs in product feature discovery and roadmap prioritization through validating product hypotheses, designing success metrics and quantifying end user impact
• Collaborate with domain experts to validate findings and ensure alignment with real-world applications.
• Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions, continuing to foster our culture of Applied Science excellence
• On-call duties

About you:

• Master’s or Ph.D. in Computer Science, Data Science, Mechanical Engineering, Electrical Engineering, or a related field with a focus on condition monitoring or machine learning applications.
• 5+ years of proven programming skills using standard ML tools such as Python, PyTorch, Tensorflow etc.
• Strong foundational knowledge in machine learning, data science, and statistics
• Familiarity with time-series modeling techniques and feature engineering.
• Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.

Bonus skills: 

• Hands-on experience developing models for OT and vibration analysis, condition monitoring, and fault detection or classification.
• Familiarity with signal processing techniques (e.g., Fourier transforms, wavelet analysis) and their application to OT and vibration data.

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A high impact Culture:
• You’ll work with Smart, Humble Optimists across the globe.
• Meritocratic environment where ideas and outcomes are publicly celebrated.

About us:

We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

ANALYTICS

What We Do

Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic.

What You'll Do

We are seeking a Senior Data Scientist to independently own and drive analytics initiatives for Family Experience (FamXP), Investigation analytics and Trust and Safety, with a focus on impacting team and product outcomes. You'll apply your expertise to transform ambiguous business questions into actionable insights while handling highly sensitive data with care and discretion. This role requires leading cross-functional projects, building strong stakeholder relationships across multiple teams, and maintaining the highest standards of data privacy and security. The role is expected to build foundational re-usable data models as well as end reporting and ad hoc analysis to support teams from FamXP, a product team, to Legal.

In this role, you will

• Own and deliver end-to-end analytics projects for Family Experience and Trust & Safety that drive team outcomes and measurably influence product/org outcomes, from problem framing through impact measurement; can range from telemetry implementation to reporting to automation (from Workato to ML)
• Solve ambiguous Family Experience and Trust & Safety problems by designing analyses, evaluating options/tradeoffs, and making independent decisions that keep work moving in a dynamic environment
• Execute team and product/org strategy through analytics planning: translate strategy into metrics, roadmaps/backlogs, and clear success criteria; contribute to setting team goals
• Build and maintain production-quality metrics, dashboards, and data models that monitor safety, parental controls, and age-appropriate experiences across Epic’s ecosystem
• Drive alignment around approach and outcomes with Trust & Safety, Product, Programming, Legal, and Policy partners across the team and organization, managing expectations and trade-offs
• Handle sensitive data related to minors and safety incidents with discretion, applying privacy/security best practices and Epic data governance requirements
• Mentor others on the team and within the product/org: share best practices, review work, and raise the bar for how analytics is done

What we're looking for

• 6-10 years of demonstrated ability to own and deliver analytics projects that execute team outcomes and influence product/org outcomes
• Strong SQL skills (Python, PySpark a plus) and experience working with large-scale datasets; comfort in modern data environments (e.g., Snowflake/Databricks/Spark); familiarity with version control and workflow orchestration tools (Airflow or similar) is a plus
• Proven ability to solve ambiguous problems and make independent decisions on team projects with minimal/no oversight
• Experience turning messy data into production-quality metrics, dashboards, and data models that support operational monitoring and decision-making
• Strong judgment handling sensitive or regulated data; working knowledge of privacy/security practices and relevant compliance concepts
• Ability to execute team + product/org strategy via planning and prioritization; can translate goals into measurable outcomes and help set team goals
• Track record of driving alignment and collaboration across immediate/adjacent teams and the broader product/org
• Clear communicator who can align stakeholders through concise updates and documentation that drive decisions and action
• Evidence of mentoring others on the team/product org (coaching, reviews, raising standards)
• Domain strength in Trust & Safety and/or family experiences online (e.g., moderation, account safety, community health, fraud, or safety feature measurement)

EPIC JOB + EPIC BENEFITS = EPIC LIFE

We pay 100% for benefits for both employees and dependents and offer coverage for supplemental medical, dental, vision, critical illness, telemedicine, Life and AD&D, long term disability insurance as well as weekly indemnity (short term disability) and a retirement savings plan with a competitive employer match. In addition to the EAP (employee assistance program), we also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents.

We are seeking a machine learning (ML) developer (applied research) to join our team working on the Scientist AI. In this role, you will work closely with ML research scientists and product stakeholders to start applying the Scientist AI to real-world problems.

Key responsibilities

• Accelerate applied research, model training and inference, and iterate on implementing models for real-world applications (that will form the basis of LawZero’s future solutions offerings).
• Design and implement workflows for research experiments across simulated environments and real-world applications.
• Develop datasets, tooling, dashboards, and libraries to adapt, monitor, interpret, and evaluate models in the context of real-world applications.
• Establish, document, and maintain best practices for ML model development workflows.
• Redesign and adapt research ideas and prototypes into robust production-grade tools and solutions.
• Deeply understand customer use-cases to inform training strategies and surface edge cases.
  
  

Skills and qualifications

• A degree in a relevant computer science field (e.g., computer science, computer engineering, software engineering) is required, along with an advanced degree (MSc or higher) in machine learning or equivalent work experience.
• 3+ years of industry experience in designing and implementing complex machine learning workflows on high performance computing devices using PyTorch, TensorFlow, or JAX.
• Ability to collaborate effectively with cross-functional teams, document best practices, and stay updated with the latest advancements in ML and software development.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and workload managers (e.g., Ray, SLURM)
• Familiarity with containerization tools (e.g., gRPC, Docker, Kubernetes).
• Familiarity with data infrastructures and platforms (e.g., vector databases).
• Experience building new ML products from scratch, or based on research prototypes.
• Experience working alongside researchers is a bonus.

What we offer

• The opportunity to contribute to a unique mission with a major impact.
• Comprehensive health benefits.
• A minimum of 20 days vacation per year upon start.
• A minimum retirement savings employer contribution of 4%.
• Generous flexible benefits designed to contribute to your well-being.
• A team of passionate experts in their field.
• A collaborative and inclusive work environment with offices in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation.

We are seeking a Machine Learning (ML) Research Scientist to join our team working on a novel AI safety agenda. In this role, you will design and implement innovative ML models aimed at solving advanced AI safety problems.

Key responsibilities

• Propose, design, and implement novel ML models tailored to solve complex AI safety problems.
• Collaborate with mathematicians and other specialized research scientists to integrate theoretical advancements into practical ML algorithms and models.
• Adapt and fine-tune existing frontier models to enhance their applicability to specific settings.
• Design and implement experimental protocols and evaluation frameworks to validate hypotheses and ensure robust and reproducible results, including at the scale and complexity of frontier models.
• Analyze and interpret experimental data in order to steer future research questions and objectives.
• Benchmark and optimize model performance and efficiency along with ML engineers to ensure the optimal usage of computing resources over the course of long experiments.
• Communicate findings and synchronize work with other researchers and engineers.

Required skills and qualifications

• Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but not required if the candidate demonstrates exceptional abilities.
• 3-5 years of experience in deep learning research projects, in particular with frontier models.
• Proven experience in the training, adaptation, and/or fine-tuning of frontier models across a variety of complex scenarios that involve, for example, transfer learning, domain adaptation, or meta learning.
• Expertise in the integration and use of ML libraries such as PyTorch, TensorFlow, or JAX for the development, training, and evaluation of ML models, ideally in distributed computing environments.
• Strong experience in Python software development, in the use of version control, collaboration tools, and experiment management and tracking tools.
• Strong communication skills, both written and verbal, with the ability to exchange ideas with researchers across different disciplines.
• Ability to work collaboratively in a team environment while also being self-motivated and independent.

Preferred skills and qualifications

• Experience analyzing the behavior of frontier models in safety-critical contexts.
• Experience in the design and development of model alignment strategies or benchmarks.
• Experience with natural language processing or probabilistic graphical models.
• A track record of contributing to high-quality research projects in deep learning.

What we offer

• The opportunity to contribute to a unique mission with a major impact.
• Comprehensive health benefits.
• A minimum of 20 days vacation per year upon start.
• A minimum retirement savings employer contribution of 4%.
• Generous flexible benefits designed to contribute to your well-being.
• A team of passionate experts in their field.
• A collaborative and inclusive work environment with offices in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation.

Shape the future of enterprise AI technology

Do you want to turn cutting-edge natural language processing into products impacting millions of users?

As a Senior II Applied Scientist on Coveo’s Knowledge AI team, you will help build the language technologies at the core of our generative artificial intelligence platform.

You’ll take on a technical leadership role, influencing our NLP vision while designing, evaluating, and deploying advanced solutions such as retrieval augmented generation pipelines, information retrieval, semantic search, question answering, and agentic systems, always with real-world constraints in mind.

As one of our Senior II Applied Scientists, you will:

• Design, develop, and optimize modern language-based artificial intelligence solutions, from data and modeling choices to evaluation strategies and production constraints.
• Apply and serve transformer-based language models at scale, delivering reliable, real-time experiences to enterprise users.
• Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles.
• Act as a technical reference within the team, guiding architectural decisions and promoting best practices in applied science.
• Mentor applied scientists, supporting their growth and helping raise the overall level of expertise within the group.
• Contribute to research and development processes that foster efficiency, rigor, and a culture of applied science excellence.
• Share our innovations externally through technical blog posts, presentations, or other thought leadership content.

Here is what will qualify you for the role:

• A PhD, or a Master’s degree with equivalent research experience, in a relevant field such as machine learning, computer science, mathematics, or physics.
• At least 8 years of industry experience applying modern natural language processing techniques, including deep learning and large language models, to real-world systems at scale.
• Strong experience designing models and systems that balance performance, user experience, and production realities.
• Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.

What will make you stand out:

• Experience in a technical leadership capacity, including mentoring, hiring, roadmap definition, or scientific project planning.
• Research or applied experience in areas closely related to Coveo’s business, such as information retrieval, neural search, semantic search, or question answering.
• Exposure to more traditional lexical or linguistics-based natural language processing techniques.
• International work experience and a demonstrated ability to collaborate across cultures and perspectives.

Do you think you can bring this role to life? Or add your own color?
You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.

Send us your application, we want to hear from you!

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.
Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.

Shape the future of enterprise AI technology

Do you want to turn cutting-edge natural language processing into products impacting millions of users?

As a Senior II Applied Scientist on Coveo’s Knowledge AI team, you will help build the language technologies at the core of our generative artificial intelligence platform.

You’ll take on a technical leadership role, influencing our NLP vision while designing, evaluating, and deploying advanced solutions such as retrieval augmented generation pipelines, information retrieval, semantic search, question answering, and agentic systems, always with real-world constraints in mind.

As one of our Senior II Applied Scientists, you will:

• Design, develop, and optimize modern language-based artificial intelligence solutions, from data and modeling choices to evaluation strategies and production constraints.
• Apply and serve transformer-based language models at scale, delivering reliable, real-time experiences to enterprise users.
• Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles.
• Act as a technical reference within the team, guiding architectural decisions and promoting best practices in applied science.
• Mentor applied scientists, supporting their growth and helping raise the overall level of expertise within the group.
• Contribute to research and development processes that foster efficiency, rigor, and a culture of applied science excellence.
• Share our innovations externally through technical blog posts, presentations, or other thought leadership content.

Here is what will qualify you for the role:

• A PhD, or a Master’s degree with equivalent research experience, in a relevant field such as machine learning, computer science, mathematics, or physics.
• At least 8 years of industry experience applying modern natural language processing techniques, including deep learning and large language models, to real-world systems at scale.
• Strong experience designing models and systems that balance performance, user experience, and production realities.
• Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.

What will make you stand out:

• Experience in a technical leadership capacity, including mentoring, hiring, roadmap definition, or scientific project planning.
• Research or applied experience in areas closely related to Coveo’s business, such as information retrieval, neural search, semantic search, or question answering.
• Exposure to more traditional lexical or linguistics-based natural language processing techniques.
• International work experience and a demonstrated ability to collaborate across cultures and perspectives.

Do you think you can bring this role to life? Or add your own color?
You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.

Send us your application, we want to hear from you!

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.
Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.

The Role

This is a full-ownership data engineering role at the center of Medeloop's AI platform. You won't be maintaining pipelines someone else built,  you'll be architecting the data backbone that powers AI agents doing real operations at scale. You'll work directly with data scientists, AI engineers, and product teams to turn raw, complex healthcare data into the clean, structured, semantically-rich foundation our AI scientists depend on. Your work shows up in customer products and research outcomes, not internal dashboards that no one reads.Candidates who currently perform these tasks exclusively through manual processes are unlikely to be suitable for this role. We require an individual who has already adopted and integrated AI techniques to enhance operational velocity, rather than one who is contemplating future experimentation.If you want to build something that genuinely changes how medical research gets done, this is the role.

What You'll Own

• The healthcare data lake: curating, extending, and evolving it through new concepts, derived variables, and data models that directly inform our AI engines and customer products
• AI-native data workflows: designing and operating AI-powered pipelines (using tools like Claude Code and agent frameworks) to automate harmonization, cleaning, quality checks, and summarization at scale
• NLP and semantic infrastructure: building pipelines for entity extraction, concept normalization, embedding-based retrieval, and semantic search that power the AI Scientist platform
• Novel data extraction approaches: experimenting with and building new methodologies for working with unstructured clinical data, not just applying existing playbooks
• Research-grade data products: delivering analytical samples, cohorts, and final datasets that withstand scientific scrutiny and are actively used by researchers and customers
• Data governance and observability protocols: including access controls, PHI/PII handling, data classification, compliance, monitoring, alerting, data freshness, and comprehensive documentation to enable self-service capabilities.

What We're Looking For

• 3+ years of relevant data engineering or data management within an analytics-driven organization, with end-to-end ownership from raw ingestion to final data product
• Deep hands-on experience with healthcare CDMs (OMOP, FHIR, PCORnet) — designing or extending them, not just querying
• Knowledge of medical ontologies: UMLS, SNOMED CT, RxNorm
• Experience with big data, data pipelines and tooling that support retrieval-augmented generation (RAG), vector integrations, embedding workflows, and other AI/ML workloads. Experience in big data tooling such as Spark, Iceberg, EMR
• Fluent in Python and SQL; comfortable across structured and unstructured data
• Proven NLP experience: semantic search, entity recognition, concept normalization, embedding pipelines
• Strong grasp of inferential statistics and cohort methodology to be a real partner to data scientists and customers (as part of onboarding)
• Experience contributing to an AI/ML product, especially in automated research or scientific discovery
• Experience mentoring other engineers and providing technical leadership

Bonus Points

• Multi-cloud experience (AWS, Azure, GCP)
• Authorship or contribution to peer-reviewed publications or technical reports

Why Medeloop

• Ownership from day one: small team, high-trust, no layers between your work and its impact
• Technically ambitious: you'll build AI-powered workflows, not just support them
• Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter
• Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build