Candidates must possess 8+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale, demonstrated experience in architecting and building identity graphs or similar identity matching solutions leveraging probabilistic techniques, strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution, proficiency in machine learning frameworks (e.g., TensorFlow, PyTo…

Candidates should possess a Bachelor’s degree in a technical field and a minimum of 8 years of industry experience, with a PhD in a relevant field potentially counting for up to 2 years of experience. Proficiency in machine learning, including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration, is required, alongside domain knowledge in credit risk, portfolio management, learning to rank, and personalization, which is considered a plus. Strong engineering …

Candidates should possess a Bachelor’s or Master’s degree in Machine Learning, Computer Science, Data Engineering, or a related field, along with proven experience in developing, optimizing, and deploying ML systems in production environments. Strong proficiency in Python, coupled with expertise in ML frameworks such as TensorFlow or PyTorch, is required, alongside extensive knowledge and hands-on experience in fine-tuning large language models for specific use cases. Clear communication skills …

Candidates must possess a Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, or Mathematics. A minimum of 7 years of experience in data science and machine learning, with a focus on real-time ML models, preferably in tech or marketplace environments, is required. Expertise in machine learning and deep learning, including a good working knowledge of large language models, is essential. Proven experience deploying impactful machine learning models into production, prof…

Candidates should have 5+ years of professional experience in data science or machine learning engineering, with proficiency in SQL and Python. Strong software engineering skills and experience building software within engineering teams are essential. Teamwork, collaboration, and communication are highly valued.

The candidate should have strong experience in training large-scale machine learning systems, particularly in STT or related speech domains. Proficiency with orchestration and infrastructure tools like Kubernetes, Docker, and Prefect, as well as familiarity with ML lifecycle tools such as MLflow, is required. Experience building internal tools or dashboards for non-technical users is also necessary.

Candidates should possess 8+ years of experience building production systems with at least 4 years focused on machine learning at scale, holding a Bachelor’s degree in Computer Science, ML, or a related field, with a Master’s degree or PhD preferred. They must have a proven track record of deploying and maintaining ML systems serving billions of requests, expertise in modern ML frameworks such as TensorFlow, PyTorch, and JAX, and strong foundations in distributed systems and cloud platforms, par…

Candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience. They are expected to demonstrate exceptional problem-solving abilities and strong communication skills to influence decisions and drive alignment across teams. A minimum of 5 years of experience in building and delivering robust, scalable, and highly reliable services in production environments is required, along with a deep passion for technical exce…

Candidates must possess 8+ years of experience in applied Machine Learning, holding a Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Deep expertise in mainstream RecSys model architecture, strong proficiency in Python and ML frameworks like PyTorch, JAX, or TensorFlow, and extensive experience building performant machine learning systems at scale are essential. Excellent communication, collaboration, and problem-solving skills are req…

Candidates must possess a PhD in Physics or a related field and have a deep understanding of machine learning algorithms and techniques, including experience in building and deploying models from scratch. Strong analytical and problem-solving skills are essential, along with a passion for the real-world application of machine learning and a desire to make a significant impact on large-scale business initiatives.

Candidates must possess a Master's or Ph.D. in Robotics, Computer Engineering, or a related field, with proficiency in both C++ and Python. A minimum of 4 years of experience in designing, training, and deploying ML models is required, along with a strong understanding of trajectory optimization, reinforcement learning, and imitation learning algorithms. Publications in Machine Learning or Robotics-related venues are also required. Bonus points include experience with autonomous driving applicat…

Candidates should possess 7-10+ years of experience in DevOps or Infrastructure Engineering, ideally with exposure to production ML systems, a Bachelor’s or Master’s degree in Computer Science or a related field, and a proven track record of enabling engineering teams by building developer-friendly infrastructure and accelerating deployment velocity. Strong experience with CI/CD tools, monitoring/alerting tools, and cloud platforms such as AWS, Azure, or GCP is required, along with bonus points …

Candidates should possess tech lead experience in a product ML team, driving research and technical direction to improve business outcomes using applied ML, experience with ads retrieval modeling, ranking, or recommendation systems, experience with deep learning models for retrieval (two tower, GNNs, transformers, LLMs), 5+ years of end-to-end experience training, evaluating, testing, and deploying machine learning models, and 2+ years of experience building machine learning models with Tensorfl…

Candidates should have 7+ years of industry experience, including several years in applied ML roles. Deep experience with DNN architectures and ML frameworks like TensorFlow or PyTorch is required, along with a strong background in recommendation systems, ads ranking, or similar domains. Experience working with large-scale datasets and complex feature pipelines, coupled with strong problem-solving and experimentation skills, is also necessary.

Candidates should have 3+ years of industry experience building and deploying production ML systems. Bonus areas of expertise include hands-on experience developing, deploying, and optimizing web-scale ML systems, experience with ML lifecycle management, personalization systems, notification optimization, and/or monetization-driven algorithms, background in recommendations, personalization, NLP, deep learning, LLM integration, or explainable AI, and familiarity building scalable ML applications …