<h3>Job Description</h3><div>Job Description<div>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 (Recommendations)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 Machine Learning Engineer to lead the development of our recommendation system driving content discovery for millions of users. As a member of a growing team, you will serve as both a technical leader that owns the entire stack for the recommendation system and as a subject matter expert on how to apply this system to the product to increase user engagement. You will work closely with the data science, product, infrastructure, and backend engineering teams to create enjoyable experiences for our users that will lead to increased customer acquisition and retention.Responsibilities:<ul><li>Design ML solutions for user problems prioritized by the team and evaluate various approaches based on viability and practicality, with consideration to project timelines and available engineering resources.</li><li>Design, develop, and deploy machine learning models to improve the accuracy and relevance of our recommendations.</li><li>Identify ways the recommendation system can be integrated into the product for maximum impact.</li><li>Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback.</li><li>Collaborate with cross-functional teams comprised of data science, backend engineering, and product management to integrate ML models into the production environment.</li><li>Ensure the scalability and efficiency of our ML systems, working closely with infrastructure teams to leverage cloud technologies effectively.</li><li>Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs.</li></ul>Qualifications:<ul><li>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.</li><li>Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow.</li><li>Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions.</li><li>Proven track record of leading projects and delivering impactful machine learning solutions.</li><li>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.</li></ul>Nice to have:<ul><li>Experience with Amazon SageMaker or similar MLOps platforms.</li></ul>More about PhiloAt Philo, we're a company that puts people first—both our subscribers and our team. Our philosophy is to empower our colleagues to do their best work while supporting each other in pursuing shared goals. We value pragmatism, pride in our work, and passion. Transparency and openness are fundamental to our company culture. We are committed to diversity and inclusion as we grow the Philo team and shape the future of TV. We believe that a diverse set of voices and perspectives on our team enables us to innovate faster and create the best experience for our subscribers.Philo offers access to top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery, Food Network, Hallmark, HGTV, History, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, WE tv, and more, along with groundbreaking originals and blockbuster movies included with AMC+. Our service also includes 80+ free channels and premium add-ons like STARZ and MGM+.Our extensive library boasts over 75,000 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 and Cambridge, MA. Our leadership team includes a co-founder of Facebook and alums from Meraki and HBO, backed by NEA and industry partners like 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 Compensation: Includes annual salary between $200K - $240K depending on experience and location, company stock options and health benefits.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:<ul><li>Full health, dental and vision coverage for you and your family</li><li>401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)</li><li>Flexible working hours</li><li>Up to 20 weeks of fully paid parental leave</li><li>Unlimited paid time off for vacation and sick leave</li><li>$2,000 annual vacation bonus (we pay you to take a two week vacation)</li><li>$5,250 annually for professional development and educational assistance</li><li>$1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)</li><li>$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)</li><li>Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps</li><li>Dog-friendly office</li><li>And much more!</li></ul>For California Residents: Philo's CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and ContractorsPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</div></div>

<h3>Job Description</h3><div>Job Description<div>#TeamNextdoorNextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 315,000 neighborhoods across 11 countries.Meet Your Future NeighborsAt Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including newsfeed, notifications, ads relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. The Impact You'll Make<ul><li>You will be part of a scrappy and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis. Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform</li><li>Collect and gather datasets to build machine learning (ML) models that make real-time decisions for the Nextdoor platform</li><li>Analyze datasets and and use important features to build low-latency models for decisions that need to be made quickly</li><li>Deploy ML models into production environments and integrate them into the product</li><li>Run and analyze live user-facing experiments to iterate on model quality by measuring impact on business metrics</li><li>Collaborate with other engineers and data scientists to create optimal experiences on the platform</li></ul>What You'll Bring To The Team<ul><li>B.S. in Computer Science, Applied Math, Statistics, Computational Biology or a related field</li><li>7+ years of industry/academic experience of applying machine learning at scale</li><li>Experience of building ML models for advertising products</li><li>Proven engineering skills. Experience of writing and maintaining high-quality production code</li><li>Ability to work with and analyze large amounts of data</li><li>Ability to succeed in a dynamic startup environment</li></ul>RewardsCompensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package.The starting salary for this role is expected to range from $190,000 to $355,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. Compensation may also vary by geography.We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date.Overall, total compensation will vary depending on your relevant skills, experience, and qualifications.We have you covered! Nextdoor employees can choose between a variety of great health plans. We cover 100% of your personal monthly premium for health, dental, and vision – and provide a OneMedical membership for concierge care.At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.#LI-Hybrid</div></div>

<h3>Job Description</h3><div>Job Description<div>#TeamNextdoorNextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on.Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 315,000 neighborhoods across 11 countries.Meet Your Future NeighborsAt Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including newsfeed, notifications, ads relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. The Impact You'll Make<ul><li>You will be part of a scrappy and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis. Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform</li><li>Collect and gather datasets to build machine learning (ML) models that make real-time decisions for the Nextdoor platform</li><li>Analyze datasets and and use important features to build low-latency models for decisions that need to be made quickly</li><li>Deploy ML models into production environments and integrate them into the product</li><li>Run and analyze live user-facing experiments to iterate on model quality by measuring impact on business metrics</li><li>Collaborate with other engineers and data scientists to create optimal experiences on the platform</li></ul>What You'll Bring To The Team<ul><li>B.S. in Computer Science, Applied Math, Statistics, Computational Biology or a related field</li><li>7+ years of industry/academic experience of applying machine learning at scale</li><li>Experience of building ML models for advertising products</li><li>Proven engineering skills. Experience of writing and maintaining high-quality production code</li><li>Ability to work with and analyze large amounts of data</li><li>Ability to succeed in a dynamic startup environment</li></ul>RewardsCompensation, benefits, perks, and recognition programs at Nextdoor come together to create one overall rewards package.The starting salary for this role is expected to range from $213,000 to $355,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. Compensation may also vary by geography.We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date.Overall, total compensation will vary depending on your relevant skills, experience, and qualifications.We have you covered! Nextdoor employees can choose between a variety of great health plans. We cover 100% of your personal monthly premium for health, dental, and vision – and provide a OneMedical membership for concierge care.At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.#LI-Hybrid</div></div>

Machine Learning Engineer Jobs in Bodega Bay, CA

Sr Machine Learning Engineer Recommendations
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August 31, 2024

Sr Machine Learning Engineer Recommendations
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Senior Staff Machine Learning Engineer Ads
August 15, 2024

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Machine Learning Engineer Jobs in Bodega Bay, CA

Sr Machine Learning Engineer RecommendationsSeptember 4, 2024

Senior Staff Machine Learning Engineer AdsAugust 31, 2024

Sr Machine Learning Engineer RecommendationsAugust 15, 2024