Role Description Für alle, die nicht nur mitlaufen, sondern den Takt angeben. AImera Group ist eine technologiegetriebene IT-Boutique für Machine Learning, Data Products und skalierbare Software. Wir liefern maßgeschneiderte Lösungen direkt bei unseren Kunden - schnell, pragmatisch und mit echtem Business-Impact. Du willst nicht nur Code schreiben, sondern Projekte vorantreiben, Kunden überzeugen und Verantwortung übernehmen? Dann bist du bei uns genau richtig. Aufgaben - Sehr gute Python-Kenntnisse und Erfahrung mit gängigen ML-Frameworks (z. B. PyTorch, TensorFlow) - Starkes Verständnis für Daten, Modelle, Deployment und produktionsreife ML-Systeme - Erfahrung mit Pipelines, Git, Docker und modernen Entwicklungsprozesse - Sicheres Auftreten beim Kunden: Du kannst komplexe Dinge einfach erklären und Vertrauen aufbauen - Kommunikativ, überzeugend und lösungsorientiert - du kannst dich und deine Arbeit beim Kunden „verkaufen” - Struktur, Ownership, Drive - du arbeitest selbstständig, schnell und verlässlich Nice to have: - Cloud- & MLOps-Erfahrung - Erfahrung mit nicht-technischen Stakeholdern - Interesse an Deep Learning, Active Learning oder generativen Modellen - Ein gutes Gespür für Business-Relevanz und pragmatische Entscheidungen Qualifications - Mindestens 7 Jahre einschlägige Berufserfahrung im Bereich Machine Learning, Data Engineering oder Softwareentwicklung - Sehr gute Deutschkenntnisse auf C2-Niveau (schriftlich und mündlich) Benefits - Projekte mit echtem Impact - Top-Vergütung - transparent, fair und leistungsorientiert - Ein Team, das dich pusht - nicht bremst Company Description Let’s build.

Opportunity Overview: We are looking for a Machine Learning Engineer ll to join our team! Our ML team’s work is focused on designing, deploying, and monitoring production models which extract or predict relevant clinical findings from structured and unstructured data sources. In this role, you’ll join our growing team of world-class engineers, statisticians, and clinical experts to deploy machine learning algorithms that help automate burdensome administrative clinical practices. You will be tasked with finding the most promising opportunities for impact and then delivering on them. This is a unique opportunity to join a high caliber engineering team that is growing quickly. You will build impactful healthcare technology on a modern tech stack. What you’ll do: - Perform in-depth analysis of healthcare data to independently design, develop, and deliver clinical ML models. - Build reliable and scalable production machine learning systems - Work on feature engineering, statistical analysis, developing novel ML techniques, understanding performance, and improving model run time. - Work cross-functionally across diverse stakeholders, including product managers, statisticians, clinicians, and clinical analysts. What you’ll need: - You have 2-4 years full time professional experience in Machine Learning - You have an MS in computer science, machine learning, computational linguistics, statistics, mathematics or similar field - You have hands on experience building with modern language models, including context-engineering LLMs or fine-tuning SLMs - You understand scientific best practice in experimental design and can independently perform data collection, measurement, and interpretation of results - You have experience configuring, training, evaluating, deploying, and maintaining models in a production setting - Advanced proficiency in Python and familiarity with ML frameworks such as PyTorch. Pay & Perks: 💻 Fully remote opportunity with about 5% travel 🩺 Medical, dental, vision, life, disability insurance, and Employee Assistance Program 📈 401K retirement plan with company match; flexible spending and health savings account 🏝️ Flexible Time Off + Company Holidays 👶 Up to 14 weeks of paid parental leave 🐶 Pet insurance  The salary range for this position is $119,000 - $140,000 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment. Interview Process*: - Connect with Talent Acquisition for a Preliminary Phone Screening - Meet your Hiring Manager! - Behavioral Interview(s) - Live Coding - Case Study *Subject to change About Cohere Health: Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members. With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately. Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes. The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone. We can’t wait to learn more about you and meet you at Cohere Health! Equal Opportunity Statement: Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal. #LI-Remote #BI-Remote

At Philo, we’re a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we’re building the TV experience that we’ve always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences. Senior Machine Learning Engineer (Recommendation Systems)Philo’s recommendation system improves user engagement and customer satisfaction by tailoring content discovery to individual preferences and viewing habits. We want users to be confident that Philo will have something they want to watch every time they open the app. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users. In this role, you will research, design, and build advanced algorithms and large-scale systems that power Philo’s recommendation engine. As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention. Responsibilities: - Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization. - Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas. - Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment. - Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement. - Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models. - Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback. - ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs. - Explore advanced architectures: Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus. Qualifications: - 8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus. - Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow. - Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions. - Proven track record of leading projects and delivering impactful machine learning solutions. - Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly. - Experience with Amazon SageMaker or similar MLOps platforms More about Philo At Philo, we’re a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture. We’re committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We’re committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email recruiting@philo.com and we’ll work with you to meet your needs. Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+. Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast. Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E. Join us at Philo and be part of a team that's shaping the future of TV! Status: Full-time Location: San Francisco, CA or remote within the U.S. Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location: - San Francisco, New York City: $175K - $235K - Boston, DC Metro, Los Angeles, Seattle: $165K - $225K - Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $155K - $215K - Texas, Florida: $150K - $205K We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team: - Full health, dental and vision coverage for you and your family - 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay) - Flexible working hours - Up to 20 weeks of fully paid parental leave - Unlimited paid time off for vacation and sick leave - $2,000 annual vacation bonus (we pay you to take a two week vacation) - $5,250 annually for professional development and educational assistance - $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter) - $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco) - Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps - Dog-friendly office - And much more! For California Residents: Philo’s CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It's transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We're not waiting for the future to arrive. We're shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Senior Machine Learning Engineer on the Personalization team, you'll shape how players experience our products by building real-time, one-to-one personalization at scale. You'll design and deploy machine learning systems that deepen engagement, improve retention, and drive long-term player value. Working across Engineering, Product, and Analytics teams, you'll turn data into impactful experiences while advancing how we build, deploy, and optimize ML solutions. This role blends hands-on model development with system design and technical leadership in a fast-moving, high-impact environment. What You'll Do - Lead end-to-end machine learning initiatives focused on improving player engagement and retention, from initial concept through production deployment. - Build scalable, reusable machine learning pipelines with a focus on reliability, maintainability, and performance. - Design and manage CI/CD workflows for machine learning using tools like MLflow, Jenkins, and GitOps to enable automated and efficient model deployment. - Monitor model performance in production, implementing retraining strategies, drift detection, and continuous optimization. - Partner with cross-functional teams to translate business goals and user insights into high-impact machine learning solutions. - Mentor other engineers and help define best practices for machine learning system design, development, and deployment. What You'll Bring - Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field. - At least 3 years of experience working with machine learning systems in production environments. - Strong proficiency in Python and SQL, with experience working on distributed data platforms such as Spark. - Proven experience delivering production-grade machine learning models that drive measurable business impact. - Hands-on experience with Databricks for managing machine learning workflows, model lifecycle, and collaborative development. - Experience designing experiments and analyzing A/B tests to validate and optimize model performance. - Strong communication and collaboration skills, with experience mentoring or leading technical initiatives. Join Our Team We're a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don't worry, we'll guide you through the process if this is relevant to your role.