About Path robotics

Path Robotics is redefining what's possible in autonomous welding. Our AI-powered robotic welding systems use advanced sensing and computer vision to adapt in real time — no fixtures, no programming, no limits. We're building the future of manufacturing, and we're looking for engineers who want to get their hands dirty doing it.

The Role

We're looking for a Software Engineer with strong systems-level instincts and experience building software that interfaces directly with hardware. You'll work across our sensing stack, robotic platform, and compute infrastructure — writing the code that lets our robots see, move, and think. This is a role for someone who's comfortable working close to the metal: writing HALs, integrating sensors and actuators, and squeezing performance out of embedded compute platforms.

What You’ll Do

• Develop full-stack software for sensing and robotic systems, including HALs for cameras, laser sensors, and communication interfaces.
  
  
• Build and extend the software architecture that integrates robotic arms, welding systems, and peripheral hardware into a unified control stack.
  
  
• Design and implement robust device drivers, HALs, and ROS-based components for production robotic applications.
  
  
• Develop and optimize software for embedded compute platforms such as NVIDIA Jetson, including real-time and GPU-accelerated workloads.
  
  
• Work closely with hardware, firmware, and systems teams to bring up devices, debug issues across the stack, support deployments, and improve field performance.

Who You Are

• 3–6 years of software engineering experience in robotics, automation, embedded systems, or a related field.
  
  
• Strong C++ skills in production environments, with working knowledge of Python for tooling, scripting, and testing.
  
  
• Hands-on experience with ROS or ROS2 in deployed systems.
  
  
• Experience building HALs, device drivers, or other low-level software for sensors, actuators, and hardware peripherals.
  
  
• Comfortable with embedded Linux, cross-compilation, and working alongside hardware and firmware engineers to debug integrated systems.

Why You’ll Love Working Here

• Competitive salary and equity in a well-funded, high-growth robotics company
• Comprehensive health, dental, and vision benefits
• 401(k)
• Flexible PTO
• Hands-on, collaborative culture

*Path Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.*

Who We Are

Build the Path Forward

At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

We’re looking for a Software Engineer with deep experience in C++ and Python to lead the development of core systems powering our intelligent robotic platforms. In this role, you’ll architect and implement high-performance software at the intersection of real-time robotics, perception, and machine learning. You’ll take technical ownership of critical components, mentor team members, and help shape the future of our robotics software stack.

What You’ll Do

• Drive software architecture decisions across robotics and perception systems.
• Design, implement, and optimize performance-critical components of the robotics and perception stack in C++ and Python.
• Develop and integrate 3D point cloud processing algorithms for weld joint perception, including registration, pose estimation, segmentation, and geometric reasoning.
• Lead the integration of machine learning models into real-time systems, ensuring low-latency, high-reliability performance.
• Design and implement gRPC/Protobuf service interfaces with attention to schema versioning and backward-compatible API evolution.
• Instrument perception systems for production observability, building telemetry pipelines that connect algorithmic metrics to business outcomes.

Who You Are

• Bachelor's, Master's, or PhD in Computer Science, Robotics, Electrical Engineering, or a related field.
• 5+ years of professional experience in software engineering; title and compensation will be commensurate with experience.
• Solid grasp of system-level software design, concurrency, memory management, and optimization.
• Advanced proficiency in modern C++ and Python, with demonstrated experience building production services using gRPC and Protobuf.
• Experience with robotics or perception applications, including familiarity with ROS/ROS2, motion planning, and hardware interfaces is preferred.
• Proficient in Linux-based development; experience with Docker strongly preferred

Why You’ll Love Working Here

• Daily free lunch to keep you fueled and connected with the team
• Flexible PTO so you can take the time you need, when you need it
• Comprehensive medical, dental, and vision coverage
• 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
• 401(k) retirement plan through Empower
• Generous employee referral bonuses—help us grow our team!

Who We Are

About Path robotics

Path Robotics is redefining what's possible in autonomous welding. Our AI-powered robotic welding systems use advanced sensing and computer vision to adapt in real time — no fixtures, no programming, no limits. We're building the future of manufacturing, and we're looking for engineers who want to get their hands dirty doing it.

The Role

We're looking for a Software Engineer to build and maintain the infrastructure that powers our AI and machine learning workflows. You'll be the bridge between our AI research team and production — building the tooling, pipelines, and deployment systems that let models go from experiment to factory floor. This is a role for someone who thinks in systems but speaks ML: you understand what researchers need, and you know how to build reliable software around it.

What You’ll Do

• Build and maintain the software infrastructure that supports robot learning, including model training, experiment tracking, versioning, and deployment.
  
  
• Develop pipelines and tools for collecting, processing, and curating large-scale robotic sensor and telemetry data.
  
  
• Support deployment of AI models onto robotic systems, including simulation, hardware integration, runtime monitoring, and feedback loops from field data.
  
  
• Build internal tools that accelerate AI engineering workflows across dataset exploration, testing, evaluation, and productionisation.
  
  
• Partner closely with AI researchers and robotics engineers to turn model requirements into robust, scalable software systems.

Who You Are

• You have 3–6 years of software engineering experience, with solid exposure to ML infrastructure, MLOps, or AI-enabled systems.
  
  
• You write strong production software in Python, and ideally also have experience with C++, ROS, or robotics software stacks.
  
  
• You have experience with PyTorch and a practical understanding of the software systems needed to support AI model development.
  
  
• You are comfortable with data pipelines, simulation environments, containerised workflows, and GPU compute in Linux environments.
  
  
• You enjoy working across AI and robotics, and can support the full path from data collection and testing through to deployment on real systems.

Why You’ll Love Working Here

• Competitive salary and equity in a well-funded, high-growth robotics company
• Comprehensive health, dental, and vision benefits
• 401(k)
• Flexible PTO
• Hands-on, collaborative culture

*Path Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.*

Who We Are

Build the Path Forward

At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

We’re looking for a Software Engineer with deep experience in C++ and Python to lead the development of core systems powering our intelligent robotic platforms. In this role, you’ll architect and implement high-performance software at the intersection of real-time robotics, perception, and machine learning. You’ll take technical ownership of critical components, mentor team members, and help shape the future of our robotics software stack.

What You’ll Do

• Drive software architecture decisions across robotics and perception systems.
• Design, implement, and optimize performance-critical components of the robotics and perception stack in C++ and Python.
• Develop and integrate 3D point cloud processing algorithms for weld joint perception, including registration, pose estimation, segmentation, and geometric reasoning.
• Lead the integration of machine learning models into real-time systems, ensuring low-latency, high-reliability performance.
• Design and implement gRPC/Protobuf service interfaces with attention to schema versioning and backward-compatible API evolution.
• Instrument perception systems for production observability, building telemetry pipelines that connect algorithmic metrics to business outcomes.

Who You Are

• Bachelor's, Master's, or PhD in Computer Science, Robotics, Electrical Engineering, or a related field.
• 5+ years of professional experience in software engineering; title and compensation will be commensurate with experience.
• Solid grasp of system-level software design, concurrency, memory management, and optimization.
• Advanced proficiency in modern C++ and Python, with demonstrated experience building production services using gRPC and Protobuf.
• Experience with robotics or perception applications, including familiarity with ROS/ROS2, motion planning, and hardware interfaces is preferred.
• Proficient in Linux-based development; experience with Docker strongly preferred

Why You’ll Love Working Here

• Daily free lunch to keep you fueled and connected with the team
• Flexible PTO so you can take the time you need, when you need it
• Comprehensive medical, dental, and vision coverage
• 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
• 401(k) retirement plan through Empower
• Generous employee referral bonuses—help us grow our team!

Who We Are

Build the Path Forward

At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

We are standing up a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing. 

We are seeking a Senior Machine Learning Engineer (Tech Lead) for this new team. You write code, set the technical direction, make the architectural decisions the team builds on, mentor junior and intermediate engineers, and help shape how the team works.

What You’ll Do

• Set the ML technical direction for the team, architectural choices on perception, reasoning, and action generation; training methodology; data strategy; the path from research bet to deployed capability. As one of the first senior hires, you are designing the approach, not extending it.
• Own the architectural workstreams that define the team's research and engineering bets — multiple core build streams across action-policy learning, world-model-based supervision, and policy-orchestration interfaces.
• Design hybrid physics-ML architectures for the integrated loco-manipulation stack. Manipulation, locomotion, and the whole-body control coupling between them are not separable on legged platforms; sub-millimetre continuous-trajectory precision at the tool requires the whole-body controller to compensate for base motion in real time. Today on fixed bases; tomorrow on mobile platforms. The integration is the hard problem; you own its design.
• Own the cross-functional partnerships with hardware teams, domain experts, customer-facing assurance standards, and upstream / downstream teams. Drive a phased deployment strategy that builds production trust over time.
• Mentor and shape the team, guide junior and intermediate ICs across software, ML, robotics, and perception backgrounds; establish code-quality standards, review practices, and engineering norms; help identify and attract next hires. You write code throughout — this is a tech-lead role, not a step away from the work.

Who You Are

• Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field or equivalent experience.
• 5+ years of hands-on robot learning experience. You have shipped sim-to-real policies on real robots, across different tasks or platforms.
• Demonstrated technical leadership and mentorship. You have made architectural decisions on robot learning systems that others built on, and you have meaningfully shaped the development of more-junior engineers as a tech lead. This can be in academia (leading a lab subgroup, advising students) or industry.
• Deep sim-to-real expertise — domain randomisation, system identification, teacher-student distillation, sim-to-online fine-tuning. You can design a transfer strategy for a novel problem.
• Full-stack robot learning — fluent across simulation construction, policy training, data collection, real-world deployment, and failure diagnosis.
• Physics-informed ML or hybrid control experience — PINNs, neural ODEs, MPC with learned dynamics, process-model-conditioned generation, or similar.
• A defensible view on visual-reasoning-centric substrates for grounded spatial / physical reasoning.
• Push-back willingness — you can defend a non-obvious architectural commitment under pressure, and change your mind on evidence.
• Strong programming skills in Python and C++; production-quality code with reproducibility, testing, and maintainability discipline.
• Strong communication skills, able to convey complex technical concepts to a diverse audience.
• Demonstrated independent technical authority — you have set technical direction in a tech-lead capacity, leading a research subgroup, owning an architecture across multiple ICs' work, or making the architectural call on a high-profile project.

Strongly Preferred:

• Edge inference depth (TensorRT, ONNX, edge-class deployment).
• Loco-manipulation experience — locomotion, whole-body control, and manipulation on legged platforms (quadrupeds, humanoids). The coupling between the three is the hard problem; direct hands-on experience or a defensible architectural view both count.
• Precision manipulation or surgical robotics — sub-mm accuracy tasks.
• Flow-matching action-head design at depth — direct experience with the architectural pattern.
• Visual self-supervised representation learning experience on robot or 3D-vision tasks.
• Multi-skill workflow or hierarchical policy design — skill sequencing, failure detection, control mode transitions.
• Experience building ML capability from early stage — first or second ML engineer on a team, or built a research group's infrastructure from scratch.

Why You’ll Love Working Here

• Daily free lunch to keep you fueled and connected with the team
• Flexible PTO so you can take the time you need, when you need it
• Comprehensive medical, dental, and vision coverage
• 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
• 401(k) retirement plan through Empower
• Generous employee referral bonuses—help us grow our team!

Who We Are

At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive 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.

If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact HR@path-robotics.com. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Columbus_OH

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Seattle

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

Note: Benefits may vary by location and are subject to local regulations.

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Vancouver_Canada

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_NewYork_NewYork

POSITION TITLE: Software Engineering Instructor 

REPORTS TO: Manager Director

LOCATION: Columbus, OH 

WHO WE ARE LOOKING FOR: 

Per Scholas is seeking a Technical Instructor to deliver high-end technical training to underemployed and unemployed community residents for purposes of higher economic development and improvement of quality of life. The Technical Instructor must be self-directed and self-motivated, and comfortable with making intermediate-level decisions to adapt processes and curriculum delivery based on current conditions. The Technical Instructor works in collaboration with peers with learner support and works with the Managing Director to change policies, procedures, and strategic planning. 

WHAT YOU’LL DO: 

• Deliver technology skills training and assessments to prepare students for entry-level to mid-level careers in the field of software development  Daily instruction, assessment administration, attendance, one-on-one tutoring, evaluation, and monitoring of individual student progress 
• Be Adept in learning new software tools, languages, and technologies as needed. 
• Work closely with the team to identify student needs, provide the necessary support, and establish individualized plans for student achievement 
• Tutor students as needed 
• Work with Career Advance team to ensure alumni are completing additional requirement
• Maintain Salesforce database with student scores and attendance 
• Work with Career Advancement team to ensure volunteers from the business community interact with students as classroom speakers, mentors, and small group coaches 
• Work with Career Advancement team to recommend students for particular employment opportunities 
• Monitor student compliance to attendance and other program policies, and address violations with students in a consistent manner. Work with Manager, Career Advancement to ensure documents such as probationary and termination letters are prepared and delivered. 
• Connect students with the resources necessary for them to overcome their individual barriers to maintaining success in school 
• Create, submit and maintain training curricula for approval and school files. 
• Work closely with the Program Design team to create student content on the PS Academy. 
• Instructors will need to commit a few hours per week to preparing lessons and materials, leveraging existing PS curriculum content. 
• Work closely with co-instructors or teaching assistants to provide students with meaningful and prompt feedback on their progress. 

WHAT YOU’LL BRING TO US: 

Professional Requirements 

• You have at least 2+ years of experience working on a software development team.
• You have working experience in both front-end and back-end development, and are fluent in:
• HTML5 and CSS3
• Full-stack JavaScript (strong JavaScript highly preferred)
• At least one JS MV* framework (Angular, Backbone, or React preferred)
• SQL databases (we generally use PostgreSQL)
• NoSQL (we generally cover MongoDB)
• Express/Node.j
• A Bachelor’s (or Master’s) degree in a related field is preferred but not required. 
• Experience with curriculum, syllabus development, and lesson planning.
• Experience with student assessment; and a talent to continuously evaluate the curriculum to identify what is working and what improvements can be made 
• Qualified candidates must be able to comfortably and frequently lift 50lbs

Personal Characteristics 

• You thrive in a creative, inventive, fast-paced startup environment with people who are passionate about their work and mission. 
• You are data-driven, result-oriented and a forward-looking catalyst for social change. 
• You have a collaborative and flexible work style. You’re excited to work cross-functionally with other departments and independently. 
• You are an effective communicator with strong oral and written skills. 
• You are tech savvy and can learn fast. 
• You are strong at managing your time and you can balance multiple projects and tasks. 
• You stand behind our mission, believing that individuals from any community should be able to access well-paying career positions, and that talent should be recognized and recruited from many diverse sources.

For this role specifically, we are targeting a salary of $70,000/year, with a range between $65,000/year and $75,000/year, where the difference in salary is typically determined by several factors, including geography in which the selected candidate resides, and alignment with qualifications and experience.

#LI-Onsite

Position Summary

Join MyFundedFutures as a senior, hands-on engineer to design, build, and maintain our core backend systems, platform infrastructure, and frontend tools.  Someone who takes strong, informed positions on architecture and technology options, while remaining pragmatic and adaptable to the realities of a fast-moving trading platform business.

You thrive in environments where financial accuracy, system uptime, and developer productivity are equally critical and you treat dependability as a non-negotiable professional standard.

Key Responsibilities

• Serve as the technical lead across platform and backend engineering — owning architecture decisions, facilitating cross-team coordination, and ensuring consistent development standards.
• Design, build, and maintain core backend services and APIs using Django/Python and Go, with a focus on reliability, performance, and scalability.
• Proactively identify and address technical debt, performance bottlenecks, security risks, and reliability gaps before they become production incidents.
• Mentor and develop engineers across the team — providing clear, constructive technical guidance and helping others grow in ownership and scope.
• Contribute to frontend development in React, particularly around platform integrations and internal tooling.
• Be a dependable presence on-call and in production — you take ownership of issues through to resolution and document your learnings as repeatable processes.

Qualifications

Required

• Strong ability to write well-structured, idiomatic, Python and Go with a deep understanding of the Django ecosystem.
• Hands-on experience integrating payment systems (Stripe, Worldpay, Braintree, or similar)
• Demonstrated ability to lead technical architecture discussions and produce clear, defensible design decisions with appropriate trade-off analysis.
• Experience with RESTful API design, WebSockets, and asynchronous/event-driven architectures.
• Strong understanding of databases (PostgreSQL, MySQL, Elasticsearch) including schema design, query optimization, indexing and transactional integrity.
• Proficiency with CI/CD pipelines, automated testing strategies, and modern DevOps tooling.
• React (or similar) development experience — comfortable contributing to or reviewing frontend work within a full-stack platform context.
• Reliable and dependable – you follow through, communicate proactively, and treat your commitments seriously.
• Strong written and verbal communication skills; comfortable driving alignment across engineering, product, and business stakeholders.

Preferred

• Background in trading, futures, prop trading, or fintech environments — you understand the domain, the stakes, and the performance expectations.
• Experience with Kubernetes and container orchestration in production environments.
• Familiarity with distributed systems patterns: message queues (Kafka, RabbitMQ), caching strategies (Redis), and service-to-service communication.
• Experience operating in multi-team engineering organizations with shared codebases or platform dependencies.
• Exposure to observability tooling: Prometheus, Grafana, structured logging, and distributed tracing.

Software Engineering Intern - AI Data Operations
HumanSignal | Columbus, Ohio | Hybrid | Spring/Summer 2026

About Us
HumanSignal builds Label Studio Enterprise, the data annotation platform trusted by Fortune 500 companies including Apple. We're expanding our 400+ person Columbus facility and need engineering talent to build systems that power AI training pipelines.

What You'll Build

• Full-stack web applications for crowdsourced data collection with quality control workflows
• Admin dashboards with bulk operations, analytics, and workflow management
• Data pipelines integrating Label Studio, AWS S3, and automated quality checks
• JSON transformation systems processing thousands of annotation files for enterprise clients

Technical Skills (Strong in Several Required)

• Frontend: React, TypeScript, responsive UI, state management
• Backend: Python (data processing, APIs, automation), RESTful design
• Data: Database design, JSON manipulation, multi-status workflows
• Deployment: Vercel, serverless functions, CI/CD

Bonus: AWS S3, email integration, real-time updates, admin dashboards

Who You Are

• Ohio State engineering student (CS, Software Engineering, Data Science, or related)
• Can architect solutions and ship working code autonomously
• Comfortable with full-stack development and data pipelines
• Interested in AI infrastructure and training data systems

Details

• Location: Hybrid in Columbus (2-3 days/week in-office)
• Compensation: $35-50/hour based on experience
• Schedule: Flexible part-time or work-study arrangements
• Duration: Minimum 12 weeks, potential for extension/conversion

To Apply
Email resume, GitHub, and brief note to careers@humansignal.com including:

• A technical challenge you've solved with data or workflows
• Your availability and preferred start date

HumanSignal is committed to building a diverse team. We encourage applications from candidates of all backgrounds.
We're moving fast—strong candidates will be interviewed on a rolling basis.

Company Overview

Regent’s Retail Services Group (RSG) is a shared operational infrastructure that supports Regent’s portfolio of retail businesses, including La Senza, Club Monaco, Escada, and Drybar. RSG is designed to provide centralized, best-in-class functional expertise that enables Regent’s brands to focus on growth, transformation, and long-term value creation.

Regent is a global private equity firm focused on acquiring complex and underperforming businesses and driving their exponential growth through operational improvements and strategic capital deployment. Regent’s portfolio spans retail, consumer, media, and industrial sectors, with a strong emphasis on hands-on operational leadership.

Position Overview

Regent’s Retail Services Group (RSG) is seeking an experienced Director of HR and Recruiting to lead and oversee all aspects of human resources for RSG and its supported retail businesses. This is a full-stack HR leadership role responsible for building, operating, and continuously improving core HR functions while serving as a trusted advisor to senior leaders and business partners.

Based in Columbus, OH, this role will own end-to-end HR strategy and execution for RSG, including employee relations, HR systems, compliance, communications, organizational planning, and talent-related processes. The HR Director will play a critical role in enabling scalable growth, operational rigor, and a high-performance culture across Regent’s retail platform.

Key Responsibilities

• Serve as the senior HR leader for RSG, acting as a strategic business partner and trusted advisor to executive leadership and functional leaders
• Provide expert guidance on company policies, employee relations, performance management, and employment practices
• Own and continuously improve core HR processes, including onboarding, offboarding, performance reviews, compensation planning, and employee lifecycle management
• Lead employee relations matters, including investigations, issue resolution, performance management, and corrective actions
• Oversee benefits administration and vendor relationships, ensuring competitive, compliant, and cost-effective programs
• Manage and optimize HR systems and data (HRIS), ensuring data integrity, reporting accuracy, and scalable processes
• Ensure compliance with all federal, state, and local employment and labor laws; partner with legal as needed
• Partner with Talent Acquisition and lead workforce planning, recruiting strategies, and organizational growth needs
• Provide input and leadership on organizational design, workforce planning, and change management initiatives
• Develop and deliver clear, effective internal HR communications in partnership with leadership
• Support leaders in building high-performing teams through coaching, feedback, and development initiatives
• Maintain high standards of confidentiality, professionalism, and judgment in all HR matters

Qualifications

• Bachelor’s degree in Human Resources, Business Administration, or a related field
• 8+ years of progressive HR experience, including leadership responsibility across multiple HR disciplines
• Proven experience operating as a full-scope HR leader in a multi-site or multi-business environment
• Strong working knowledge of employee relations, compensation, benefits, performance management, and organizational development
• Demonstrated experience with HRIS platforms (experience with ADP, Workday, or similar systems preferred)
• Comprehensive knowledge of federal, state, and local employment and labor laws
• Ability to partner effectively with senior leaders while managing competing priorities across multiple stakeholders
• Strong judgment, discretion, and ability to handle sensitive and complex employee matters
• Highly organized with exceptional attention to detail and execution focus
• Excellent written and verbal communication skills
• Self-starter with a hands-on mindset and comfort operating in fast-paced, evolving environments

Compensation and Benefits

• Salary range: $120,000-130,000 + discretionary bonus
• Comprehensive benefits package including Medical, Dental, Vision, and 401(k) participation.
• Additional perks: Health Savings Account (HSA), Short/Long-Term Disability, Life Insurance, Commuter Benefits, and Employee Discount Programs.