Duties: You will use your expertise on large-scale machine learning platform infrastructure, and integrate with state-of-art visual recognition technologies, to build a highly scalable deep learning infrastructure. We have aggressive growth goals so the ability to lead a team down the line is a real possibility
Requirements: MS/PhD in Computer Science; Strong C/C++ or Java experience; Knowledge of UNIX systems; Strong knowledge of large-scale machine learning platforms infrastructure

Duties: Inform, influence, support, and execute our product decisions through data; Research applied data science questions in our ads system to improve prediction accuracy, develop data-driven go-to-mark strategies, and drive advertiser value; Work closely with engineering and product teams to develop hypotheses, run experiments and prototype new product ideas; Collaborate with data engineering teams to build/maintain reports, dashboards, and metrics to monitor the performance of our products, provide insights and identify new opportunities
Requirements: 5+ years of experience working in an analytics organization, ideally in Tech industry leading companies, especially in the advertising area; Ads or Advertiser or Agency experience; Advanced degree (PhD, MS or BS) in Statistics, Mathematics, Economics, Computer Science or other quantitative fields; Sustained track record of driving business value and improving product with data insights, especially in advertising, growth, marketing or relevant domains; Experience with ML and statistical knowledge, fluency in Python, SQL, Scala or other programming languages

Duties: Develop, Train, Finetune, and Deploy large language models for text completion and chats in different applications including coding, NLU, NLG, IRQA, machine translation, and dialog, reasoning, and tool systems; Apply instruction tuning, reinforcement learning from human feedback (RLHF), and parameter efficient finetuning such as p-tuning, adaptors, Lora, and so on to improve LLMs for different use cases; Measure and benchmark model and application performance; Analyze model accuracy and bias and recommend the next course of action & Improvements; Maintain model evaluation systems
Requirements: Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 3+ years of experience; Excellent programming skills in Python with strong fundamentals in programming, optimizations and software design; Strong knowledge of ML/DL techniques, algorithms, and tools with exposure to CNN, RNN (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs); Hands-on experience on conversational AI Technologies like Natural Language Understanding, Natural Language Generation, Dialog systems (including system integration, state tracking and action prediction), Information retrieval and Question and Answering, Machine Translation etc

Duties: As a Principal Machine Learning Engineer, you will drive the development and implementation of the cutting-edge machine learning algorithms, collaborating with business, engineering, and analytics teams, to build large-scale recommendation systems to recommend the best content, notifications and actions to our customers. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI/ML's transformative potential is realized across our offerings
Requirements: Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience); 8+ years of related industry experience in the machine learning domain; Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks); Experience building and scaling machine learning models in business applications using large amounts of data

Duties: Participate in the whole scope of our application development where you will be working closely with our team in the design and implementation of algorithms, tools and methodologies in speech research, voice interface design, application prototyping, and development of our proprietary speech recognition engine Take part in extending and improving components of our speech understanding platform
Requirements: PhD in relevant discipline is highly desirable, but others with strong academic backgrounds and equivalent experience are encouraged to apply; A very strong machine learning background with deep structured learning/hierarchical learning and statistical modeling techniques that can be applied to speech; Strong software engineering skills in one or more of the following: Java, Python, and C++; Solid experience with building automatic speech recognition systems that can be integrated in an information retrieval process; Solid experience with Kaldi

Duties: Develop safety evaluation frameworks that are critical to ML model improvements; Design and implement robust data analysis pipelines and validation frameworks; Develop and apply statistical methods and ML models to analyze historical/simulation data and assess safety performance; Collaborate with cross-functional teams like Simulation and Planning to ensure comprehensive safety evaluation across the autonomous driving system
Requirements: PhD in a quantitative field (IE Statistics, Mathematics, Physics); 3+ years of industry experience solving large-scale complex problems; Proven expertise using advanced statistical methods (e.g., ML models, hypothesis testing, causal analysis); Ability to interpret and work with data in the presence of ambiguity (e.g., confounding factors, data sparsity or quality challenges); Demonstrated knowledge of Python/SQL/R data analysis libraries and packages

Duties: Collaborate with ML practitioners to understand their models and modify model architectures to run faster on the car; Build tools to benchmark and analyze workloads; Build tools to improve model latency and quality; Build tools to productize deep learning models for onboard and offboard deployment
Requirements: BS in Computer Science, Mathematics or a related field; 5+ years of industry experience; C++ programming skills; Passion for developing and optimizing ML software stacks for modern architectures (framework, runtime library, ML compiler, efficient deep learning)