Derq is an MIT spinoff building AI-powered traffic safety and smart infrastructure. We\u00e2\u0080\u0099re a team of passionate innovators, leveraging the latest in AI and technology to transform the future of mobility. Our platform enhances road safety and traffic management by turning real-time data into actionable insights for cities and road operators. Our patented technology collects and analyzes data from connected sensors like cameras, radar, and traffic signal controllers to help predict and prevent road incidents. We deploy edge and cloud solutions that make intersections and highways safer and smarter.<\/p>
<\/p>Role Overview
As a ML Quality Assurance Engineer at Derq, you will play a critical role in ensuring the reliability, accuracy, and performance of our computer vision and machine learning based products. You will work closely with our development team to design and execute comprehensive test strategies, identify and report defects, and help improve the overall quality of our customer facing AI products, using data analytics.<\/p>
<\/p>Key Responsibilities
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.<\/p>
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This is a rare chance to apply frontier sequential recommendation architectures to real enterprise problems at scale. You will own applied ML work end-to-end for recommendation system workloads, adapting Liquid Foundation Models for customers who need personalization and ranking capabilities that run efficiently under production constraints.<\/p>
Unlike most recommendation roles that are siloed into a single product surface, this role gives you full ownership over how large-scale recommendation models are adapted, evaluated, and deployed for enterprise customers. Between engagements, you will build reusable applied tooling and workflows that accelerate future delivery.<\/p>
If you care about data quality at scale, user behavior modeling, and making recommendation systems actually work in enterprise production environments, this is the role.<\/p>
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We need someone who:<\/p>
Takes ownership: <\/strong>Owns customer recommendation system engagements end-to-end, from requirements through delivery and evaluation.<\/p><\/li> Thinks at scale: <\/strong>Can reason about user interaction data, sequential modeling, feature engineering, and evaluation across large-scale production systems.<\/p><\/li> Is pragmatic: <\/strong>Optimizes for measurable customer outcomes (engagement, conversion, revenue lift) over theoretical novelty.<\/p><\/li> Communicates clearly: <\/strong>Can translate between customer business metrics and internal technical decisions, and push back when needed.<\/p><\/li><\/ul> <\/p> Act as the technical owner for enterprise customer engagements involving recommendation and ranking workloads<\/p><\/li> Translate customer requirements into concrete specifications for recommendation models<\/p><\/li> Design and execute data pipelines for user interaction data, feature engineering, and training data curation at scale<\/p><\/li> Fine-tune and adapt large-scale sequential recommendation models (e.g., HSTU-style architectures) for customer-specific use cases<\/p><\/li> Design task-specific evaluations for recommendation model performance (ranking quality, latency, throughput) and interpret results<\/p><\/li> Build reusable applied tooling and workflows that accelerate future customer engagements<\/p><\/li><\/ul> <\/p> Must-have:<\/strong><\/p> Hands-on experience building or fine-tuning recommendation models at scale (not just off-the-shelf collaborative filtering)<\/p><\/li> Experience with sequential recommendation architectures, user behavior modeling, or large-scale ranking systems<\/p><\/li> Strong intuition for data quality and evaluation design in recommendation contexts (offline metrics, A\/B testing, business metric alignment)<\/p><\/li> Experience with large-scale data pipelines for user interaction data and feature engineering<\/p><\/li> Proficiency in Python and PyTorch with autonomous coding and debugging ability<\/p><\/li><\/ul> Nice-to-have:<\/strong><\/p> Experience with transformer-based recommendation architectures (HSTU, SASRec, BERT4Rec, or similar)<\/p><\/li> Experience delivering recommendation systems to external customers with measurable business outcomes<\/p><\/li> Familiarity with serving recommendation models under latency and throughput constraints<\/p><\/li><\/ul> <\/p> Independently owns and delivers enterprise recommendation system engagements with minimal oversight<\/p><\/li> Is trusted by customers as the technical owner, demonstrating strong judgment on the tradeoffs between model quality, latency, and business impact<\/p><\/li> Has built reusable applied workflows or tooling that accelerate future customer engagements<\/p><\/li><\/ul> <\/p> Real ML work: <\/strong>You will build and adapt large-scale recommendation models for enterprise customers, working with frontier architectures like HSTU under real production constraints.<\/p><\/li> Compensation: <\/strong>Competitive base salary with equity in a unicorn-stage company<\/p><\/li> Health: <\/strong>We pay 100% of medical, dental, and vision premiums for employees and dependents<\/p><\/li> Financial: <\/strong>401(k) matching up to 4% of base pay<\/p><\/li> Time Off: <\/strong>Unlimited PTO plus company-wide Refill Days throughout the year<\/p><\/li><\/ul> At Trunk Tools, we\u00e2\u0080\u0099re the leading AI company revolutionizing construction, the second-largest industry on earth. We recently raised a $40M Series B led by Insight Partners, bringing our total funding to $70M from top-tier investors including Redpoint and Innovation Endeavors. This new round is fueling our next phase of growth as we scale AI agents across the jobsite.<\/p> Our mission is to build the future of construction through intelligent automation. Despite being a $13+ trillion industry, construction still runs largely on analog processes, we\u00e2\u0080\u0099re changing that by embedding AI directly into field operations.<\/p> Founded by builders and technologists (Stanford, MIT), our team has delivered software used by over 140,000 field professionals, impacting millions of users and contributing to $10B+ in built projects. Many of us come from the field ourselves, giving us a deep understanding of the industry\u00e2\u0080\u0099s unique challenges.<\/p> After years of building the \u00e2\u0080\u009cbrain\u00e2\u0080\u009d of construction, we\u00e2\u0080\u0099re now launching production-ready AI agents, starting with intelligent document processing and Q&A, and rapidly expanding into core operational workflows. Our team has doubled in the past year, and with 65+ employees (25+ engineers), we\u00e2\u0080\u0099re scaling fast and entering a period of hypergrowth. This is a rare opportunity to join at an inflection point.<\/p> Own and evolve core parts of our AI platform, spanning search, retrieval, and multi-agent orchestration.<\/p><\/li> Lead the design and build-out of a multi-agent system, including defining new agent \u00e2\u0080\u009cpillars\u00e2\u0080\u009d and how they collaborate in production.<\/p><\/li> Architect and scale document processing pipelines (Kubernetes-based), including ingestion, parsing, chunking, indexing, and structured data extraction across heterogeneous document types.<\/p><\/li> Design and iterate on search and retrieval systems (ranking, query understanding, QA) grounded in real user behavior and product needs.<\/p><\/li> Help build and expand our knowledge graph, modeling entities and relationships to power downstream reasoning and retrieval.<\/p><\/li> Drive ambiguous, high-impact projects end-to-end, from problem definition through experimentation and productionization.<\/p><\/li> Establish and improve evaluation and experimentation frameworks to measure system quality and guide iteration.<\/p><\/li> Write clean, maintainable, production-grade code and raise the bar for engineering quality across the team.<\/p><\/li><\/ul> 7+ years of experience building and shipping production ML\/AI systems.<\/p><\/li> Proven track record of leading complex, ambiguous projects<\/strong> and driving them to impact.<\/p><\/li> Strong experience with agentic systems, LLM-based applications, or orchestration frameworks.<\/strong><\/p><\/li> Deep experience in document processing pipelines<\/strong> (e.g., parsing, chunking, indexing, structured extraction), ideally in distributed systems (Kubernetes or similar).<\/p><\/li> Experience building or working with knowledge graphs \/ provenance graphs<\/strong> and modeling relationships between entities.<\/p><\/li> Background in one or more of: search\/ranking systems, NLP, recommendation systems, or large-scale data\/ML infrastructure.<\/p><\/li> Strong coding skills (Python, Go, or similar) with an emphasis on production systems.<\/p><\/li> Highly analytical, product-minded, and comfortable using data to drive decisions.<\/p><\/li> Bonus<\/em>: experience in construction or other document-heavy industries.<\/p><\/li><\/ul> What we offer<\/strong><\/p> \u00f0\u009f\u008e\u0096\u00ef\u00b8\u008f A close-knit and collaborative early-stage startup environment where every voice is heard and every opinion matters<\/p> \u00f0\u009f\u0092\u00b0 Competitive salary and stock option equity packages<\/p> \u00f0\u009f\u008f\u00a5 4 Medical Plans to choose from including 100% covered option. Plus Dental and Vision Insurance!<\/p> \u00f0\u009f\u00a4\u0093 Learning & Growth stipend <\/p> \u00f0\u009f\u008f\u00a0 Flexible long-term work options (remote and hybrid)<\/p> \u00f0\u009f\u00a5\u00a8 Free lunch provided in the office in NYC & Austin - you\u00e2\u0080\u0099ll never go hungry with us! <\/p> \u00f0\u009f\u009b\u00ab Unlimited PTO; We truly believe in work-life balance and that hard work should be balanced with time for rest and rejuvenation<\/p> \u00f0\u009f\u008f\u009d IRL \/ In-Person retreats throughout the year<\/p> <\/p> Please note:<\/strong> All official communication from Trunk Tools will come from an email address ending in @<\/strong><\/em>trunk.tools<\/strong><\/em><\/a>. If you receive outreach from any other domain, please disregard it or report it to us.<\/em><\/p> <\/p> At Trunk Tools, we\u00e2\u0080\u0099re working hard to build a more productive and safer environment within the construction industry, and we strive to live by these same values here at Trunk Tools HQ. As an equal-opportunity employer, we are committed to building an inclusive environment where you can be you. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, or any other legally protected class.\u00c2\u00a0<\/em><\/p> This role is for one of our clients Compensation: <\/strong>Rs. <\/strong>6500 per hour hour (20 hours per week commitment) Job Type:<\/strong> Part-time \/ Contract<\/p>\n <\/p>\\n <\/p> <\/p>\\n We are seeking a highly motivated and detail-oriented Tax AI Expert<\/strong> to join our team at the intersection of taxation, data, and emerging technologies. This role is ideal for professionals with a strong foundation in tax principles who are eager to leverage artificial intelligence to optimize tax processes, enhance compliance, and support strategic decision-making.<\/p>\n<\/div>\n<\/section>\n Healthcare is in crisis and the people behind the results deserve better. With more and more data coming from wearables, lab tests, and patient\u00e2\u0080\u0093doctor interactions, we\u00e2\u0080\u0099re entering an era where data is abundant.<\/p> Junction is building the infrastructure layer for diagnostic healthcare, making patient data accessible, actionable, and automated across labs and devices. Our mission is simple but ambitious: use health data to unlock unprecedented insight into human health and disease.<\/p> If you're passionate about how technology can supercharge healthcare, you\u00e2\u0080\u0099ll fit right in.<\/p> Backed by Creandum, Point Nine, 20VC, YC<\/strong>, and leading angels, we\u00e2\u0080\u0099re working to solve one of the biggest challenges of our time: making healthcare personalized, proactive, and affordable. We\u00e2\u0080\u0099re already connecting millions and scaling fast. Short on time? TL;DR<\/strong><\/p> You:<\/strong> Can define what should be measured, how it should be modeled, and how those insights should shape product and company decisions.<\/p><\/li> Ownership:<\/strong> You\u00e2\u0080\u0099ll own Junction\u00e2\u0080\u0099s highest-leverage statistical, modeling, and evaluation work across diagnostics, clinical workflows, and AI-enabled product development.<\/p><\/li> Scope:<\/strong> This is not a pure IC modeling role and not a reporting role. You\u00e2\u0080\u0099ll set the methodology, research roadmap, and decision framework for how Junction uses data to drive product, clinical, and business outcomes.<\/p><\/li> Salary:<\/strong> $180,000 \u00e2\u0080\u0093 $220,000 + equity<\/p><\/li> Location:<\/strong> Fully remote (EST timezone only)<\/p><\/li><\/ul> <\/p> Why we need you<\/strong><\/p> Junction sits in the flow of high-value diagnostics and clinical data. As the company grows, our advantage moves beyond just having data to having the ability to turn it into reliable intelligence improving product decisions, customer outcomes, and the performance of the business.<\/p> Some of that work exists today, but it is not yet owned as a coherent function. Models get built. Analyses get done. Experiments answer local questions. But we need someone who can define the broader scientific and analytical system: what we should measure, what methods we trust, where modeling creates real leverage, and how that work translates into products and decisions that hold up outside a demo.<\/p> We\u00e2\u0080\u0099re hiring our first Data Scientist to take ownership of, and establish that standard.<\/p> This role will lead Junction\u00e2\u0080\u0099s most important modeling, experimentation, and evaluation work. You\u00e2\u0080\u0099ll partner closely with data, product engineering and leadership teams to drive the analytical roadmap by which Junction can leverage differentiated value from data.<\/p> <\/p> What you\u00e2\u0080\u0099ll be doing day to day<\/strong><\/p> Own the research and modeling work underlying Junction\u00e2\u0080\u0099s highest-priority data science opportunities across diagnostics, clinical workflows, and AI-enabled product features<\/p><\/li> Define rigorous frameworks for measurement, experimentation, and causal evaluation so we can distinguish signal from noise and make decisions we can defend<\/p><\/li> Lead development of predictive models, segmentation approaches, risk or routing logic, and other statistical systems that directly inform product and business strategy<\/p><\/li> Build the analytical foundation behind customer-facing features \u00e2\u0080\u0094 from model development through to validation and performance tracking<\/p><\/li> Partner with engineering and data engineering to ensure models and analytical systems can be put in production, are reliable, and useful in real workflows<\/p><\/li> Establish how Junction evaluates data-driven and AI-enabled features, including methodology, quality thresholds, monitoring, and performance review<\/p><\/li> Communicate complex technical findings clearly to technical and non-technical stakeholders, including tradeoffs, limitations, and implications for action<\/p><\/li><\/ul> <\/p> Requirements<\/strong><\/p> Strong track record of leading high-stakes analytical work that influenced product, operational, or business decisions<\/p><\/li> Deep foundation in statistical inference, experimental design, observational analysis, and model evaluation<\/p><\/li> Strong Python and\/or R skills, with experience working on large, messy real-world datasets<\/p><\/li> Experience building predictive or decision-support models in production or near-production environments<\/p><\/li> Experience partnering closely with engineering to move work from analysis or prototype into deployed systems<\/p><\/li> Ability to operate at both strategic and hands-on levels: defining the roadmap while also getting into the details when needed<\/p><\/li> Strong communication and stakeholder management skills; able to explain methods, findings, and tradeoffs to executives as well as technical peers<\/p><\/li> Comfort operating in a startup environment with ambiguity, limited structure, and high ownership<\/p><\/li><\/ul> <\/p> Nice to have<\/strong><\/p> Experience designing, executing, and publishing research studies<\/p><\/li> Experience with HIPAA, PHI, or other regulatory clinical frameworks<\/p><\/li> Deep familiarity with modern data tooling and production workflows across warehouses, orchestration, and transformation layers<\/p><\/li> Experience developing, deploying, and designing evaluation frameworks for LLM or AI-powered features in customer-facing products<\/p><\/li> Expertise directly working with healthcare, diagnostics, lab data, wearable data, and other clinical data<\/p><\/li> Experience applying causal inference methods, such as diff-in-diff, propensity scoring, or instrumental variables in practice<\/p><\/li><\/ul> <\/p> What this role isn\u00e2\u0080\u0099t<\/strong><\/p> Not an analytics role focused on dashboards, reporting, or one-off analysis<\/p><\/li> Not an ML platform role \u00e2\u0080\u0094 you won\u00e2\u0080\u0099t own infrastructure or tooling<\/p><\/li> Not a good fit if you mainly want to experiment with models or AI ideas without being accountable for how they perform in production<\/p><\/li> Not a good fit if you struggle with ambiguity. Knowing what to work on is part of the job<\/p><\/li><\/ul> <\/p> How you'll be compensated<\/strong><\/p> Salary: $180,000 \u00e2\u0080\u0093 $220,000 + equity<\/p><\/li><\/ul> Your salary is dependent on your location and experience level<\/p><\/li> Generous early stage options (extended exercise post 2 years employment) <\/p><\/li> Regular in-person offsites, last were in Tenerife and Miami<\/p><\/li> Monthly learning budget of $300 for personal development and productivity<\/p><\/li> Flexible, remote-first working - including $1K for home office equipment<\/p><\/li> Monthly budget of $150 to use towards a coworking space<\/p><\/li> 25 days off a year + national holidays<\/p><\/li> Healthcare coverage depending on location<\/p><\/li><\/ul> <\/p> Oh and before we forget: <\/strong><\/p> Backend Stack: Python (FastAPI), Go, PostgreSQL, Google Cloud Platform (Cloud Run, GKE, Cloud BigTable, etc), Temporal Cloud<\/p><\/li> Frontend Stack: TypeScript, Next.js<\/p><\/li> API docs are here: https:\/\/docs.junction.com\/<\/a><\/p><\/li> Company handbook is here<\/a> with engineering values + principles<\/p><\/li><\/ul> <\/p> Important details before applying:<\/strong><\/p>The Work<\/strong><\/h2>
Desired Experience<\/strong><\/h2>
What Success Looks Like (Year One)<\/strong><\/h2>
What We Offer<\/strong><\/h2>
<\/strong>Reflection\u00e2\u0080\u0099s mission is to build open superintelligence and make it accessible to all<\/strong>.
We\u00e2\u0080\u0099re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.
We're always open to great people. If you're aligned with our mission but don't see the right role, we'd love to hear from you.
What We Offer
<\/strong>We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.
We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
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<\/strong>Job Type: Contractor
<\/strong>Location: Remote
<\/strong>Job Summary
<\/strong>Join our customer team as a Data Scientist and play a pivotal role in transforming data into actionable insights that drive business growth. You will leverage your expertise in statistics, mathematics, and programming to tackle challenging data problems, ensuring clean, robust, and insightful analyses. This is an exciting opportunity to work in a dynamic, expert-driven environment that values clear communication and innovative thinking.
Key Responsibilities
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<\/strong>Job Type: Contractor
<\/strong>Location: Remote
<\/strong>Job Summary
<\/strong>Join our customer team as a Data Scientist and play a pivotal role in transforming data into actionable insights that drive business growth. You will leverage your expertise in statistics, mathematics, and programming to tackle challenging data problems, ensuring clean, robust, and insightful analyses. This is an exciting opportunity to work in a dynamic, expert-driven environment that values clear communication and innovative thinking.
Key Responsibilities
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<\/li><\/ul>Required Skills And Qualifications
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<\/li><\/ul>Preferred Qualifications
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