Are you passionate about pushing the boundaries of machine learning? Do you thrive on solving complex problems and developing groundbreaking technologies that shape the future? If so, we want to hear from you!
We are looking for a talented Core ML Researcher to join our innovative team, where you will play a pivotal role in developing cutting-edge machine learning models and algorithms that will power our next-generation products. This role is perfect for someone who loves working at the intersection of research and application, crafting algorithms that don’t just perform well but drive impactful, real-world change.
Key Responsibilities:
Innovative Research: Dive into the latest advancements in Core Machine Learning (ML) techniques, and explore novel algorithms, frameworks, and architectures that can solve challenging problems.
Model Development: Design, prototype, and implement robust machine learning models and systems that will be directly integrated into high-impact products.
Optimization & Scalability: Work on improving the performance, efficiency, and scalability of existing ML models, making them ready for large-scale deployment.
Collaboration: Work closely with cross-functional teams including product managers, software engineers, and data scientists to translate research findings into deployable solutions.
Experimentation & Benchmarking: Conduct experiments, run benchmarks, and analyze data to evaluate model performance. Continuously iterate to improve accuracy, speed, and overall impact.
Technical Leadership: Act as a subject matter expert, mentoring junior team members and fostering a collaborative, knowledge-sharing environment within the team.
Qualifications:
Educational Background: Ph.D. or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with a deep understanding of statistical learning, optimization, and advanced ML techniques.
Experience: Proven experience in Core ML research, algorithm development, and the deployment of machine learning systems. Ideally, experience in neural networks, deep learning, reinforcement learning, or natural language processing (NLP).
Technical Expertise: Strong proficiency in programming languages such as Python, C++, or Java. Familiarity with ML frameworks like TensorFlow, PyTorch, or similar.
Problem-Solving Mindset: Ability to approach complex problems with creativity, critical thinking, and a hands-on approach to problem-solving.
Collaboration Skills: Excellent communication and teamwork skills, with the ability to collaborate effectively in cross-disciplinary teams.
Key Skills: