London, UK We're building the future of Revenue Management. AI agents that give short-term rental operators and independent hotels more money for less effort. We integrate directly with Booking.com, Airbnb, and PMS platforms via deep private API connections. The role: This is a flexible Hybrid role in London. You'll be the second engineering hire, working directly alongside Martin. Everything is on the table: backend systems, React frontend, Chrome extension, data pipelines, agent orchestration, and prompt engineering. You'll ship full features end-to-end, not tickets. We ship fast using Claude Code and AI-assisted development daily. If you're already running multiple PRs in parallel with AI tools, you'll feel right at home. What we offer: £80K–£90K base salary plus up to 1% equity (DOE). This is a founding role, you'll have real ownership of the product and the company. You'll shape technical direction, product decisions, and company culture from the ground floor. If you want to build something real with a small team that's already winning customers and growing fast, where your code ships to production the same day and your decisions shape the company then let's talk. What we're looking for: Previous startup or founder experience, you've built something from zero and know what that demands. Very strong Python (Django/Celery) and React. Comfortable across the full stack, backend, frontend, infra, data. AI agent development, prompt engineering, or data pipeline experience is a strong plus. You need to be based in London or able to come to our Canary Wharf office 2 days a week. We can't sponsor visas. Stack: Django, Celery, PostgreSQL, React, Chrome Extensions, Claude Code.

Suitland, MD, United States LightFront is seeking a Senior Python & SAS Developer (Data Modernization) to support a long-term Census contract. This role will focus on modernizing legacy federal statistical and survey processing workflows by translating existing logic into scalable Python-based solutions using tools such as pandas, PySpark, and modern data architecture patterns. This is a backend/data modernization role, not a traditional web application role. The developer will support legacy system analysis, backend data processing, database logic optimization, ETL and batch workflows, and cloud-based processing patterns. The work requires someone who is comfortable stepping into established systems, understanding how existing workflows operate, and carefully translating that logic into cleaner, more maintainable solutions without disrupting current operations. This role will be hired initially as a 1099 contractor under LightFront, a joint venture between Illumen Group and Spatial Front, Inc. (SFI), with the potential to convert to full-time employment in the new fiscal year. The role is remote after onboarding, but the selected candidate must report to the Census office in Maryland to retrieve equipment and complete PIV-related onboarding. If the candidate is not local, reimbursable travel will be coordinated after onboarding begins. Clearance / eligibility: Candidates must be U.S. Citizens due to federal contract requirements and must be able to obtain a Public Trust clearance. The clearance process typically takes 6–8 weeks, and candidates must be comfortable with that process and timeline before moving forward. The selected candidate will also need to report to the Census office in Maryland for equipment and PIV pickup after onboarding has started. Travel costs will be reimbursed for non-local candidates. The ideal candidate will have a strong Python background, with at least 4 years of experience in data processing, backend systems, or similar technical environments. This role requires someone who has worked with legacy systems and can translate existing business or data logic into Python-based solutions using tools such as pandas, PySpark, or similar libraries. Candidates should be comfortable working through unclear, messy, or long-standing workflows where the first step is understanding the current logic before rewriting anything. Candidates should also have at least 4 years of database experience, including writing, refactoring, or optimizing stored procedures, backend logic, and complex SQL. Experience with PostgreSQL, PL/pgSQL, Oracle PL/SQL, or similar database environments is important. The role also requires experience with data pipelines, batch processing, ETL workflows, job orchestration, troubleshooting, and performance tuning. AWS experience is also needed, ideally with services such as Lambda, SQS, SNS, IAM, or similar cloud services used in backend or data workflow environments. Linux experience is required, as the role will involve working in Linux-based development and processing environments. Experience with serverless architecture, Docker, Kubernetes, PySpark, R, or hands-on Base SAS production workflows is helpful, but not required. The strongest fit will be someone who has worked with legacy data systems, can translate existing logic rather than only build new features, is comfortable operating in less structured environments, and can balance support for older systems with modern Python, database, and cloud-based workflows.

Remote, NY, USA OPF is hiring a contract engineer to run the data collection phase of an emissions measurement study comparing edge versus cloud LLM inference across multi-modal AI workloads. The methodology is being designed by external advisors with prior published work on AI carbon measurement; the engineer's role is to implement that methodology rigorously, capture clean instrumented data, and hand it off cleanly to OPF's internal team for analysis and modeling. Findings will appear in a co-branded industry publication backed by a defensible methodology — meaning the public artifact is industry-format, but the underlying data has to withstand potential scrutiny. Engagement scope You will design, build, and run a Python-based testing harness that captures inference runtime, energy consumption, and component-level power across three edge devices and one cloud GPU instance, then deliver clean, documented outputs to the OPF analytical team for downstream modeling. The work spans Windows and Linux, three distinct hardware platforms (Intel Core Ultra with NPU, AMD Ryzen AI with XDNA NPU, NVIDIA L4 cloud GPU), multiple deployments (OpenVINO and Lemonade Server for local; vLLM, Triton, and/or FastAPI for cloud as appropriate per task); and two layers of measurement (software-based estimation and on-die telemetry). The engagement begins with a proof-of-concept phase on the AMD Ryzen 7 Pro laptop, focused on a single task (Basic Queries), to build the harness, telemetry, and methodology end-to-end before scaling to the rest of the platforms and tasks. Following this, a cloud GPU instance must be provisioned for cloud data collection and harness validation. Once the harness has been validated on one laptop and in the cloud environment, the approach will be scaled to the remaining laptops and tasks. Proof-of-concept outcome serves as an interim milestone before proceeding with the remainder of the engagement. See https://onepointfive.notion.site/job-spec-al-ml-engineer for the full job description. Required experience Strong Python proficiency, experimental discipline, and reproducibility practices Hands-on hardware telemetry — Intel RAPL, NVIDIA NVML, plus at least one of Intel SoC Watch / VTune, AMD μProf, or HWiNFO64 Working knowledge of at least one in-scope deployment (OpenVINO, Lemonade Server, vLLM, or Triton) Linux and Windows systems experience, including hardware performance counter telemetry Demonstrated reproducibility discipline: pinned environments, version-controlled configs, documented assumptions Strongly preferred Prior MLPerf Power or MLCommons Power working group submissions Published or contributed to AI energy / carbon measurement research or related sustainability topics Experience with NPU-class accelerators (Intel AI Boost, AMD XDNA, or comparable) Experience with GPU benchmarking methodology — DCGM telemetry, clock-pinning for reproducibility, or comparable practices Comfort working alongside external advisors and delivering well-documented handoffs to a downstream analytical team

San Francisco, CA, United States Metropolitan Transportation Commission (MTC) San Francisco, CA Principal Modeler – Model Development $152,501.86 - $193,409.22 Annually DEADLINE TO APPLY IS SUNDAY, JUNE 14, 2026, AT 11:55 PM The Metropolitan Transportation Commission (MTC) is the transportation planning, financing, and coordinating agency for the nine-county San Francisco Bay Area. MTC is the federally designated Metropolitan Planning Organization (MPO) and the state designated Regional Transportation Planning Agency (RTPA) for the nine-county San Francisco Bay Area. MTC provides services to the Association of Bay Area Governments (ABAG). For more information about MTC, visit www.mtc.ca.gov. EQUAL OPPORTUNITY EMPLOYER The Metropolitan Transportation Commission is an equal-opportunity, non-discriminatory employer. MTC provides all employees and applicants with an equal opportunity in every aspect of the employment experience regardless of race, color, religion, sex, sexual orientation, gender identity, age, national origin, physical handicap, medical condition or marital status. DEADLINE TO APPLY IS SUNDAY, JUNE 14, 2026, AT 11:55 PM IF YOU ARE INTERESTED, PLEASE APPLY IMMEDIATELY A resume is highly encouraged with your application. Be ready to rethink your assumptions about the public sector. Dedicated and motivated colleagues? Beautiful, high amenity building for on-site work and collaboration? Flexible schedules and hybrid work options? Yes, yes, and yes! ABOUT THE SECTION The Regional Planning Program section at MTCABAG is a multidisciplinary team that applies data-driven planning to improve the trajectory of the San Francisco Bay Area. One of our core deliverables is Plan Bay Area, which we update every four years. This long-range plan lays out a set of strategies for how to achieve a region that is affordable, connected, diverse, healthy and vibrant for all. In developing the plan, our team takes on some of the most difficult and important challenges facing the region: how to make living in the region affordable for existing and future residents, how to create a safe and effective transportation system, and how to reduce greenhouse gas emissions. The section consists of four teams: Major Plans, Transportation Planning, Housing and Local Planning, and Forecasting/Modeling and Surveys. This principal position is within the Forecasting/Modeling and Surveys (FMS) team, which conducts data analysis and develops and applies modeling tools to analyze the impacts of potential strategies for Plan Bay Area. Our team strives to create quality modeling tools that embody our sections goals for planning excellence; we emphasize transparency by creating open-source models, and we value collaboration with other agencies and partners in developing shared resources. The FMS team focuses on the application of economic models, urban development models, and travel models, including developing new features for some of these models as new analysis needs arise. FMS also conducts regular travel diary surveys and transit passenger surveys to inform these tools and other research questions of interest to the agency. ABOUT THE ROLE The Principal Modeler in Model Development will lead development of our travel modeling tools to assess our region’s future and to evaluate potential strategies and policies to improve quality of life. In this role, the Principal Modeler will manage a consulting team working in travel model development, developing both major and minor features as needed for the travel model and associated tools. This will involve project management as well as hands-on development work. The Principal Modeler will also be involved in developing other modeling and modeling-related tools relevant to long-range planning, including land use forecasting models, population synthesis tools, and others. This role will also involve working with internal and external stakeholders to prioritize feature development and bug fixes for these tools. Finally, this role will include mentoring staff in technical development, representing MTC before a variety of groups, agencies, organizations, elected officials, and the public, requiring the ability to communicate effectively about technical topics with non-technical stakeholders; and performing other job related duties as required. Responsibilities The development and release of future versions of MTC’s modeling tools, including: • Implementing or updating features • Managing a consultant team in model development and network development tools. This includes reviewing pull requests and deliverables; project and budget management; discussing and resolving budget issues with appropriate staff and responsible agencies; negotiating, preparing and administering contracts, proposals, task orders and agreements. • Model calibration, validation and documentation • Presenting Model Development progress and features to stakeholders within the agency and with agency partners. Qualifications KNOWLEDGE, SKILLS, & ABILITIES Required Deep knowledge of activity-based travel modeling and network modeling Software development skills in python to implement modeling functionality, as well as to collect, clean, code and analyze data Interpersonal skills and an ability to work in a project and team environment Desired Experience synthesizing technical information to facilitate good policy and planning decisions Data visualization experience Knowledge of the complexity of the transportation system and land use/transportation issues facing the San Francisco Bay Area MINIMUM QUALIFICATIONS Any combination of training and experience that would provide the required knowledge, skills, and abilities listed. A typical way to obtain the required qualifications would be: Education and Experience: Equivalent to a bachelor’s degree from an accredited college or university with major coursework in planning, civil engineering, environmental science, communications, business or public administration, or a related field and seven (7) years of increasingly responsible professional experience in a field related to assigned area of responsibility PREFERRED QUALIFICATIONS Education: A Bachelor's degree in an appropriate field related to the area of assignment, such as transportation planning, city and regional planning; transportation engineering or modeling, financial management, economics, business or public administration. A Master's degree is desirable. Applicants with a degree issued from an institution outside the United States must have their transcripts evaluated by an academic accrediting service and provide proof of equivalency along with their application.

Remote - London UK, United Kingdom We're an AI-driven hospitality tech platform helping vacation rental owners automate their revenue on Booking.com and Airbnb. We sit on Booking.com private API data, Airbnb channel data, and scraped competitive pricing across thousands of properties — and right now we barely use it. Our agent is rules-based where it should be data-driven, and our promotions engine has no model behind it. We're looking for a founding ML/Data Scientist to change that. You'll turn dormant data into a smarter agent and a compounding moat. The Role You'll be the first person to seriously dig into our data, find the signals that drive revenue, and work with engineering to make the agent act on them. Find what matters — dig through Booking.com, Airbnb, and competitive data to separate signal from noise. Separate cause from correlation — when a promotion drives a booking, was it causal? When occupancy drops, is it pricing, seasonality, or competition? We want rigorous answers, not guesses. Turn insights into revenue — translate findings into logic the agent can use, measurably better than a human's. Shape the data strategy — decide what to track, what to enrich, and where the highest-value opportunities are. Ship to production — this isn't a notebooks role. You'll work inside our Django + ClickHouse stack alongside the engineering team. Logistics Remote-first for UK-based candidates. Expect to be in London for WeWork sessions a few days a month, flexibly, for onboarding, planning, and product work. Interview Process 1. 30-min non-technical call with the CTO Take-home data challenge using a sample of real OTA data 1-hour deep dive on your submission with the founding team In-person meeting with both founders Offer Why This Role Unique data — Booking.com private API data, Airbnb channel data, and scraped competitive pricing. This dataset doesn't exist at most companies. Real impact — your models drive revenue decisions for thousands of properties. High equity for our stage. A compounding moat — every property we add makes the data richer and the models better. Salary £70k–£100k · Equity 0.5%–1%. Who You Are A real data scientist who reaches for statistics and experiments first, and knows when a result is significant versus noise. Strong with time series. Causal by instinct — you don't confuse correlation with causation. You can design holdouts and A/B tests, and reason about confounders when a clean experiment isn't possible. Comfortable in the mess — real OTA data is dirty, sparse, and seasonal. You wrangle it, find the signal, and build features that predict revenue. Fluent in modelling — forecasting, uplift and causal models, and the judgement to pick the simplest thing that works. Ships to production — not a notebooks role. You write clean, deployable Python (pandas, NumPy, scikit-learn) and get your models live in our Django and ClickHouse stack. A product thinker who cares about revenue impact, not what's technically interesting. AI-first — you use AI coding tools with multiple agents to ship faster, ideally pushing into self-learning ML or agentic workflows. If you don't already use frontier AI tools, this isn't the role for you. Skills: Python · pandas · NumPy · scikit-learn · Time Series · Causal Inference · Forecasting · Experimentation · PostgreSQL · ClickHouse · Django · AI agents

LATAM, LATAM, LATAM Crehana is a B2B SaaS platform powered by AI that delivers integrated talent management solutions to clients across Latin America — skills, learning, performance, and career development in one place. Our mission: make people development universal. We're looking for a hands-on Tech Lead. Someone who leads by example: you set the technical direction, mentor your team, and when the moment calls for it, you roll up your sleeves and write code. What you'll own: Architecture and technical decisions for scalable backend services Code quality standards, code reviews, and CI/CD practices Mentorship and growth of your engineering team Collaboration with Product and DevOps to ship impactful features Stability, security, and evolution of our platform Tech stack: Python + FastAPI (required) Docker / Kubernetes / microservices AWS, GCP, or Azure PostgreSQL, MySQL, MongoDB REST APIs / GraphQL (nice to have) Terraform (nice to have) Apply: https://www.crehana.com/p/crehana/jobs/2ca97417-9f01-48a6-a426-7950565e7672/ We're looking for a hands-on leader who still writes code when it matters. This could be someone who has already led engineering teams working with Python and modern backend stacks — or an experienced engineer with deep technical expertise who is ready to step into a leadership role for the first time. Must-have Experience leading engineering teams (junior and mid-level), or a seasoned engineer ready to take that next step Strong Python proficiency with FastAPI Hands-on experience with microservices, Docker, and Kubernetes CI/CD pipelines and automated testing practices SQL and NoSQL databases: PostgreSQL, MySQL, MongoDB Cloud platforms: AWS, GCP, or Azure Security awareness and compliance standards Strong communication, collaboration, and problem-solving skills Comfortable with agile methodologies (Scrum, Kanban) Nice to have RESTful API design and/or GraphQL Terraform for infrastructure as code

Bangalore, Pune, India We are seeking a highly skilled and innovative Python / AI Engineer to join our team and help us build the next generation of AI-powered enterprise systems. We are actively investing in LLMs, agentic workflows, and applied AI systems, but much of this potential is still untapped. Today, our AI initiatives are fragmented—PoCs exist in silos, LLM integrations are early-stage, and there is no unified intelligence layer across the application landscape. We’re looking for someone who can change that. You will sit at the intersection of engineering, R&D, and business teams, turning AI experimentation into production-grade systems that deliver measurable impact. This is not a “model training-only” role—you will be expected to design, build, and ship end-to-end AI solutions. The Role You will be the first deep technical owner responsible for turning our AI ambition into real, working systems that drive business outcomes. Build and productionize AI systems — Design and implement LLM-powered applications, AI agents, and intelligent automation workflows that integrate directly into our core product ecosystem. Develop PoCs and scale them into production — Rapidly prototype AI/ML solutions, validate feasibility with stakeholders, and evolve them into scalable, reliable services. Integrate LLMs into real business workflows — Work with APIs, orchestration frameworks, and model providers to embed LLM capabilities across applications (chat, reasoning, summarization, retrieval, and automation use cases). Design intelligent systems, not just models — Focus on end-to-end architecture: data flow, prompt orchestration, memory, evaluation, guardrails, and feedback loops. Bridge R&D and engineering — Translate research ideas and business problems into working AI systems that can be deployed, monitored, and improved iteratively. Drive AI adoption across the organization — Collaborate closely with product, engineering, and business stakeholders to identify high-impact opportunities where AI can meaningfully improve efficiency or decision-making. Skills required: 1.Minimum 8+ years of experience in AI/ML development. 2.Advanced proficiency in Python. 3.Strong understanding of AI frameworks (e.g., TensorFlow, PyTorch). 4.Expertise in at least one LLM (e.g., GPT, Claude, LLaMA). 5.Solid foundation in Data Science and statistical modeling. 6.Experience with Agentic Workflows using LangChain-based agents. 7.Hands-on experience with LangGraph (e.g., hackathons or MCPs). 8.Deep understanding of fine-tuning techniques for LLMs. 9.Hands-on experience with Transformer architecture and its evolution from earlier models. Responsibilities: 1.Design and develop PoCs and present them to business stakeholders. 2.Build and deploy innovative AI solutions using state-of-the-art models. 3.Integrate LLMs into existing and new applications. 4.Develop new functionalities within R&D applications. 5.Promote and implement best process practices across AI development workflows.