Karkidi
Staff Software Engineer, Machine Learning
Karkidi, California, Missouri, United States, 65018
The Role:
The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous.
We currently have two open Staff Software Engineer, Machine Learning positions. One is on our Recommendations team, and one is on our Trust and Safety team:
Our ML team is responsible for developing machine learning algorithms and systems for Tinder recommendations. Recommendation algorithms directly determine potential matches on Tinder and optimize the entire ecosystem to drive critical business metrics. You'll have a unique opportunity to join a company with a global footprint while working on a team small enough for you to feel the impact each day. The Trust and Safety team focuses on enhancing account authenticity, mitigating adversarial impact, building public trust, and enabling safer experiences for millions of users globally on Tinder. You will have an opportunity to work on a team that helps support one of our primary missions: ensuring that Tinder remains the safest place to meet new people.
As a Staff Software Engineer focused on recommendations, you'll play a pivotal role in shaping the future of personalized matchmaking at Tinder. Working closely with our ML team, you'll design, implement, and scale systems that influence millions of users worldwide. Leveraging cutting-edge machine learning techniques, you'll drive key innovations that enhance user experiences and improve critical business outcomes. Your work will directly contribute to optimizing our recommendation algorithms, ensuring users discover meaningful connections while balancing the ecosystem's health. With Tinder's global scale and impact, you'll be at the forefront of solving some of the most complex challenges in technology.
Where you'll work:
This is a hybrid role and requires in-office collaboration twice per week. This position is located in Palo Alto, CA.
In this role, you will:
Lead the modeling efforts of Tinder’s recommendation system or Trust and Safety experiences.
Apply state-of-the-art machine learning techniques, including deep learning, reinforcement learning, causal inference, and optimization, to enhance our foundational models.
Develop algorithms that optimize our complex ecosystem to meet multiple disparate objectives.
Lead the research and development of novel algorithms and models, staying at the forefront of advancements in ML technologies.
Work with big data to improve the accuracy and relevance of recommendations.
Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives.
Mentor and guide team members, fostering their growth and enabling them to reach their full potential.
You’ll need:
8+ years of hands-on experience in machine learning, with a proven track record of delivering impactful solutions at scale.
PhD or MS in machine learning, computer science, statistics, or another highly quantitative field.
Hands-on experience in designing and building large-scale recommendation systems and/or have trust and safety experience.
In-depth knowledge of deep neural networks, particularly in the recommendations or safety domains.
Proficiency in deep learning frameworks such as PyTorch, TensorFlow, Keras, etc.
Proficiency in Python, Java, Scala, or similar programming languages.
Strong decision-making skills with a bias for action and the ability to navigate ambiguity with confidence.
Proven leadership abilities to inspire and motivate teams to excel and achieve ambitious goals.
Salary Range:
$220,000 - $245,000 a year
Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.
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The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous.
We currently have two open Staff Software Engineer, Machine Learning positions. One is on our Recommendations team, and one is on our Trust and Safety team:
Our ML team is responsible for developing machine learning algorithms and systems for Tinder recommendations. Recommendation algorithms directly determine potential matches on Tinder and optimize the entire ecosystem to drive critical business metrics. You'll have a unique opportunity to join a company with a global footprint while working on a team small enough for you to feel the impact each day. The Trust and Safety team focuses on enhancing account authenticity, mitigating adversarial impact, building public trust, and enabling safer experiences for millions of users globally on Tinder. You will have an opportunity to work on a team that helps support one of our primary missions: ensuring that Tinder remains the safest place to meet new people.
As a Staff Software Engineer focused on recommendations, you'll play a pivotal role in shaping the future of personalized matchmaking at Tinder. Working closely with our ML team, you'll design, implement, and scale systems that influence millions of users worldwide. Leveraging cutting-edge machine learning techniques, you'll drive key innovations that enhance user experiences and improve critical business outcomes. Your work will directly contribute to optimizing our recommendation algorithms, ensuring users discover meaningful connections while balancing the ecosystem's health. With Tinder's global scale and impact, you'll be at the forefront of solving some of the most complex challenges in technology.
Where you'll work:
This is a hybrid role and requires in-office collaboration twice per week. This position is located in Palo Alto, CA.
In this role, you will:
Lead the modeling efforts of Tinder’s recommendation system or Trust and Safety experiences.
Apply state-of-the-art machine learning techniques, including deep learning, reinforcement learning, causal inference, and optimization, to enhance our foundational models.
Develop algorithms that optimize our complex ecosystem to meet multiple disparate objectives.
Lead the research and development of novel algorithms and models, staying at the forefront of advancements in ML technologies.
Work with big data to improve the accuracy and relevance of recommendations.
Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives.
Mentor and guide team members, fostering their growth and enabling them to reach their full potential.
You’ll need:
8+ years of hands-on experience in machine learning, with a proven track record of delivering impactful solutions at scale.
PhD or MS in machine learning, computer science, statistics, or another highly quantitative field.
Hands-on experience in designing and building large-scale recommendation systems and/or have trust and safety experience.
In-depth knowledge of deep neural networks, particularly in the recommendations or safety domains.
Proficiency in deep learning frameworks such as PyTorch, TensorFlow, Keras, etc.
Proficiency in Python, Java, Scala, or similar programming languages.
Strong decision-making skills with a bias for action and the ability to navigate ambiguity with confidence.
Proven leadership abilities to inspire and motivate teams to excel and achieve ambitious goals.
Salary Range:
$220,000 - $245,000 a year
Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.
#J-18808-Ljbffr