Role Description As a Principal Camera Engineer at Otto Aerospace, you will lead the development of advanced camera and sensor systems for the Phantom 3500 Super Natural Vision Infotainment System (SNVIS). This role involves: - Tracking top-level features, requirements, and specifications for camera and sensor integration. - Managing vendor engagements and driving the engineering development and review of design for all hardware and software components related to imaging and sensing technologies. - Capturing and tracking system requirements, including image quality, sensor calibration, data transmission and processing requirements, and thermal performance. - Managing interface definitions between camera and sensor systems and aircraft systems, including the Cabin Management System and avionics. This position requires a strong background in camera and sensor engineering, with experience in shipping high-quality, user-facing imaging and sensing technology products. Qualifications - Master’s degree in Electrical Engineering, Computer Science Engineering, Applied Physics or a related field. - 10+ years in camera and sensor engineering roles for shipped/released products in the aviation, consumer electronics, or related industries. - Experience shipping high-quality, consumer-facing imaging and sensing technology products. - Experience managing complex systems architecture requirements and specifications for consumer electronics product platforms or IFE/avionics platforms, including experience with: - Display panels - Touch panel system - SOCs & system I/O - Cameras, optical sensing - Inertial sensing - Audio (microphone + speaker) systems - Operating Systems and Application Software - Passion for aviation. - Proven track record of leading projects and teams in the development of imaging systems. Requirements - Expertise in camera and sensor technologies. - Strong knowledge of image processing and computer vision. - Excellent problem-solving and analytical skills. Benefits - Competitive salaries. - Subsidized medical, dental, and vision coverage. - 401(k) opportunities. - Paid short term disability. - Voluntary long-term disability and additional term life. - 15 paid days off. - 13 paid holidays. - Paid sick leave. - Potential bonuses and stock options depending on seniority and role.

Role Description As a Senior Machine Learning Engineer (individual contributor) at Revecore, you will: - Use your expertise in machine learning, exploratory data analysis, and software engineering to enhance the productivity and efficiency of our underpayment business. - Work on projects with purpose, such as prioritizing claims based on expected recovery dollars and improving our claim-remit matching process. - Own end-to-end development, training, deployment, evaluation, and improvement of machine learning systems to rank claim opportunities. - Analyze and explore data to identify actionable opportunities from internal and 3rd party data. - Research, implement, and launch new model architectures that drive business impact. - Partner and collaborate with cross-functional teams of software engineers, data engineers, subject matter experts, product managers, and analysts to design and build practical solutions. - Implement cloud MLOps and AIOps best practices to streamline the development, deployment, and maintenance of machine learning models. - Continuously measure the impact of the AI-enabled workflows on key business metrics and use these measurements to improve the machine learning models and workflows. - Learn from and teach your teammates, being the team’s expert in your specialization. - Own a workstream, being the technical lead for the workstream while partnering with others to deliver. Qualifications - A bachelor's degree in any data-centric field; scientific thinking is a must. - Experience working in a similar role, with a focus on machine learning or data science. - Experience developing and deploying machine learning models in a production environment. - Strong experience with Python, including scikit-learn; TensorFlow or PyTorch is a plus. - Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations. Requirements - An urge to question assumptions and to get it right (or at least good enough) even if your first idea is wrong. - A commitment to collaborate, rather than go off in a corner only to appear when you need to submit a pull request. Benefits - Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment. - 12 paid holidays and flexible paid time off. - 401(k) contributions. - Employee Resource Groups that build community. - Career growth opportunities. - An excellent work/life balance. Work at Home Requirements - A quiet, distraction-free environment to work from in your home. - A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required. - The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.

Role Description At Keen, the Senior Algorithms Engineer develops, deploys and improves the algorithms that run in Keen AI Cortex. You're a software engineer first, with the understanding of mathematics, data, and inference to read a model spec, question it, and suggest changes the Principal Algorithms Architect hadn't considered. You'll work directly with the Lead Engineer and Principal Algorithms Architect, taking modeling ideas from prototype to production code and contributing to the algorithms when you see a better path. What you’ll do as the Senior Algorithms Engineer: - Own algorithmic features end-to-end across the next generation of Keen's AI Cortex. Design, implement, test, ship, and watch them run in production. - Pitch in on adjacent Python backend projects (Django and FastAPI APIs, AWS infrastructure) when a piece of work spans more than one service. - Keep the engineering practices tight: code review, tests, CI gates, documentation, and a clean ticketed workflow. - Use AI coding tools with judgment. Fast iteration is the point. So is catching the moments when the model is confidently wrong. - Develop algorithms from business ideas and turn them into production code. - Collaborate with others in the development of the solutions, including the ability to effectively push back when the implementation can be improved. - Communicate clearly across Product, Research, and Engineering. Write the design doc, name the tradeoff, get the decision made. Qualifications - 7+ years shipping production Python on a team. - Knowledge of inference methods, particularly in economics and business domains including time-series models (or more generally state-space modeling), probability modeling, and multivariate systems. - Comfortable with the engineering basics: tests, CI, code review, documentation, and working out of tickets. - Hands-on experience with AWS, Docker. - Operates independently. Scopes own work, talks to stakeholders, makes judgment calls when no one else is available to make them. - Writes and speaks clearly. - Math foundation in linear algebra, probability, and statistics. Demonstrated ability to read and write mathematical specifications, interpret and improve documented solutions. - Working knowledge of pandas and NumPy, with understanding of the use of these packages in implementing algorithms. Requirements - Nice-to-have: Marketing Mix Modeling (MMM) or another econometric background. - Bayesian inference experience. - Optimization exposure. - A track record of developing mathematical algorithms into shipped production systems. Benefits - Mentoring and training from people who've been doing this for years. - Hands-on work on Bayesian models, optimization, and the data engineering behind them, applied to a product real customers use. - A seat in conversations across departments and at company-wide meetings. - 4-day work week with 3-day weekends. - Fully remote within the United States.

Role Description The Data group at Weights & Biases works across the full range of data-related topics: - Help business partners set goals, make decisions, and understand the levers to achieve their goals. - Build reporting to keep the business attuned and aligned. - Build datasets and pipelines to support self-service analysis. - Train models to understand customer growth, churn risk, and detect spam and abuse. - Explore novel benchmarks and recommendations for model training. - Build and maintain a massive data platform to power it all. As a Senior Data Platform Engineer, you will: - Partner with other Data Platform Engineers and Data Scientists to expand and maintain our data platform. - Partner with core engineering to improve our product telemetry. - Eventually, join our on-call rotation for the data platform. Strategic goals for the team over the next 12 months: - Migrate data build tools to improve efficiency and performance. - Build a robust internal data catalog and semantic layer to support self-service analytics. - Build an internal AI agent for addressing common data workflows. - Lay the foundations for internal AI applications built on top of our operational data. Qualifications - Deep knowledge (practical and theoretical) of data engineering and the accompanying workflows. - History of writing easy-to-follow code and effective documentation for your projects. - Expert knowledge of data orchestration/data pipeline tools (dbt, dagster, airflow, etc). - Experience working with large and high-demand data warehouses/platforms, multi-PB scale, and extreme business demand for the systems. - Expert knowledge and understanding of web apps and best practices for logging and event instrumentation. - Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge. Requirements - If you work well in a self-directed environment and proactively find ways to improve processes and collaborate with team members or engaged users, your initiative will really shine in this role. - You'll love this role if you enjoy connecting with real users daily, helping them solve issues, and understanding good patterns for using our tools. - Theoretical or practical knowledge of machine learning workflows and terminology. Benefits - Medical, dental, and vision insurance - 100% paid for by CoreWeave. - Company-paid Life Insurance. - Voluntary supplemental life insurance. - Short and long-term disability insurance. - Flexible Spending Account. - Health Savings Account. - Tuition Reimbursement. - Ability to Participate in Employee Stock Purchase Program (ESPP). - Mental Wellness Benefits through Spring Health. - Family-Forming support provided by Carrot. - Paid Parental Leave. - Flexible, full-service childcare support with Kinside. - 401(k) with a generous employer match. - Flexible PTO. - Catered lunch each day in our office and data center locations. - A casual work environment. - A work culture focused on innovative disruption.