Collaborate Across Functions: Work hand-in-hand with leaders across Engineering, Product Management, and Data Science to amplify the impact of AI/ML across F5 products. Hands-on experience with modern ML frameworks like PyTorch, TensorFlow, and hardware acceleration platforms (CUDA, ROCm, etc.. End-to-End Knowledge: Expertise in machine learning models, SaaS products, observability architecture, and production-scale cloud computing deployments, particularly in Kubernetes environments. Vice President, Scientific Data Strategy.. Machine Learning Software Engineering Manager
Citian is a fast growing, venture backed SaaS technology company based in Washington, DC. Our software solutions revolutionize how our transportation systems – roads, rail, transit, bicycle, pedestrian – operate. Citian is seeking to hire a Transportation Data Scientist who will play a crucial role in developing and implementing state-of-the-art machine learning models for use cases in traffic safety, mobility, and city planning. The ideal candidate will exhibit excellent knowledge of the data science and data engineering disciplines with transportation industry experience, including working with large datasets in a Python/SQL environment. Strong knowledge of Python, SQL, Python data science libraries (Pandas, Numpy, Scikit-learn, etc. Opportunity to gain valuable experience and make a significant impact in a fast growing, venture-backed tech startup
Exceptional Team: Collaborate with talented colleagues from diverse backgrounds across ML, bioinformatics, engineering, clinical operations and biology.. First-hand experience with generating biological insights from biological data (genomics, epigenetics, transcriptomics proteomics, ATAC-Seq).. Domain knowledge with advanced artificial intelligence approaches and experience applying them to a biological context.. Strong data engineering knowledge, including but not limited to experience with Spark, Hadoop, NoSQL.. You will interact with co-founders Ravi and Hannah, before meeting the technical team across a deep dive on your CV and then a round of technical and presentation challenges.
Our team of world-leading experts is developing and deploying the Nexus Layer 1 blockchain and Nexus zkVM (zero-knowledge virtual machine) in support of our mission to enable the Verifiable Internet. Strong background in information retrieval, natural language processing, or machine learning. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Knowledge of ranking algorithms, embeddings, and LLM inference/integration. Competitive salary and generous equity compensation
The mission of the Central Technology ML (CTML) team is to pioneer and implement the technology roadmap that paves the way for the future of machine learning computing on Arm architecture.. Develop an in-depth understanding of current and future ML workloads on ARM compute platforms, focusing on performance, power, and area (PPA).. A Master’s or PhD degree in Computer Engineering, Electrical Engineering, Computer Science, or related fields.. Knowledge of deep learning libraries such as TensorFlow and PyTorch.. Experience training large deep learning models on GPU-based systems.
Sustainability Science and Innovation is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise to identify, evaluate and/or develop new science, technologies, and innovations that aim to address long-term sustainability challenges.. In this role, you will leverage your breadth of expertise in data science methodologies, statistical modeling, and scientific programming to analyze complex datasets, build scientific tools, and inform sustainability strategies across carbon, waste, and water management.. Hands-on experience with advanced machine learning techniques (e.g., deep learning, reinforcement learning) and large-scale data processing, demonstrated through successful product deployments. Deep expertise in sustainability-related modeling approaches, such as emissions forecasting, techno-economic modeling, or environmental impact assessment. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
The Senior Manager, AI Product Development leads the artificial intelligence and machine learning initiatives at Ulta Beauty, directing multiple Agile PODs focused on developing AI-powered solutions. Team Management : Direct and mentor multiple Agile teams comprising data scientists, AI engineers, and ML specialists, fostering a culture of innovation, learning, and excellence in AI development. Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, etc. Ability to work effectively in an onshore/offshore development model.. Ulta Beauty is the largest North American beauty retailer and the premier beauty destination for cosmetics, fragrance, skin care products, hair care products and salon services.
Publish the research results at top-tier conferences and journals in machine learning and robotics. Ph. D. in computer science, robotics, mechanical engineering, electrical engineering, or a related field. Familiarity with deep learning platforms such as TensorFlow and PyTorch. Experience with simulation platforms and engines, such as MuJoCo, PyBullet, IsaacSym, IsaacGym, Unreal Engine. Experience in frameworks and methodologies utilized in building LLM, LVM, and LMM applications.
You will lead transformative AI initiatives that will shape the future of Smith + Nephew’s orthopedic, wound care, and sports medicine products. Act as an inspiring leader in AI, driving S+N’s innovation strategy by scouting emerging technologies and translating them into impactful solutions across orthopedics, wound care, and sports medicine. Leading development and validation of machine learning models using modern toolkits (e.g., PyTorch, TensorFlow) and statistical techniques. Expertise in machine learning, deep learning, and statistical modeling. Your Wellbeing: Medical, Dental, Vision, Health Savings Account (Employer Contribution of $500+ annually), Employee Assistance Program, Parental Leave, Fertility and Adoption Assistance Program
Dentsply Sirona develops, manufactures, and markets a comprehensive solutions offering including dental and oral health products as well as other consumable medical devices under a strong portfolio of world class brands. Make a difference -by helping improve oral health worldwide. Candidates will get to create novel products for customers of Dentsply Sirona’s cloud based platform and help further our mission – To transform dentistry and improve oral health globally. 2 to 4 years of experience with a Masters or 0 to 3 years of experience with a PhD in applying generative AI and machine learning algorithms to real-world problems.. Experience in one of the ML model development libraries: TensorFlow, PyTorch, scikit-learn, etc.
Oversee execution of this research using a broad range of analytically rigorous, quantitative and qualitative research tools, methods, and skills.. Domain expertise in one or more relevant biology domains (e.g., virology, molecular biology, computational biology, biosecurity, etc).. Proficiency in Python or other popular programming languages and machine learning frameworks (e.g. PyTorch, TensorFlow).. A PhD in Virology, Molecular Biology, Computational Biology, Biology, Biostatistics, Biosecurity, Biodefense, Artificial Intelligence, Computer Science, National Security Policy, Policy Analysis, or similar with at least 3 years of relevant professional experience. Fully remote work will also be considered.
As an Associate Director within the INDIGO | AI Innovation Lab, you will lead the development and scaling of data science capabilities while acting as a technical expert and mentor within the team.. Implement data science solutions, including but not limited to predictive models, NLP, and GenAI applications. Familiarity with cloud computing and ML platforms - AWS platform required, Dataiku and Snowflake experience preferred.. Experience with last-mile data engineering and data governance best practices (DBT preferred), including FAIR principles. Alkermes has a portfolio of proprietary commercial products for the treatment of alcohol dependence, opioid dependence, schizophrenia and bipolar I disorder, and a pipeline of clinical and preclinical candidates in development for various neurological disorders, including narcolepsy.
Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization.. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries.. Conduct objective industry, market, and sub-market analysis, including size, growth estimates, and ecosystem mapping.. Perform strategic analyses, including Porter's Five Forces and core competency alignment.. Expertise in artificial intelligence (AI) and machine learning (ML), including various applications and their relevance to electronic product development.
Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded.. Machine Learning (ML) Compiler SW Engineer in the AI group plays a crucial role in developing SW toolset to deploy cutting-edge ML inference on AMD’s Neural Processing Units (NPU).. Design tiling algorithms to map ML operators on AI Engine accelerator which powers AMD XDNA NPU.. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.
Conduct data mining using advanced techniques such as clustering, classification, and regression.. Enhance data collection and verify data integrity for analysis.. Experience with AWS SageMaker, S3, DynamoDB, RedShift, or RDS.. Knowledge of supervised and unsupervised machine learning, NLP, and data visualization tools.. Ability to obtain Public Trust Clearance.
The Senior Data Scientist will execute data science projects across the company with the purpose of solving non-routine business problems by applying advanced methods including artificial intelligence, machine learning, causal inference, advanced statistics, natural language processing and other related techniques.. The role will include the responsibility for designing and building computational models, discovering insights and identifying opportunities through the use of statistical and algorithmic methods (for instance machine learning or GenAI) as well as data visualization techniques.. Highly preferred: BSc, MSc, or PhD degree in Computer Science, Data Science, Machine Learning, or a related field such as natural sciences (Physics, Mathematics, Bioinformatics).. Minimum of 7 years of experience in data science, with expertise in GenAI, especially large language models (LLM).. Strong proficiency in programming languages for data science like Python, and ML libraries/frameworks such as Scikit-learn, TensorFlow or PyTorch.
The Kenny/Lengyel laboratory is part of the Department of Obstetrics and Gynecology/ Section of Gynecologic Oncology, studying the biology of ovarian cancer. We use a variety of cutting-edge methods, including spatial proteomics, spatial metabolomics, 3D organotypic cultures of human tissue, spatiotemporal characterization of the immune system, and stable-isotype tracing in patients. The Ovarian Cancer Research Lab at the University of Chicago is seeking a full-time, on-site Clinical Data Scientist/Analyst to support multiple research projects with an emphasis on image analysis and computational pathology and the development of AI-driven data pipelines. Analyze large-scale data (e.g., digital pathology slides) using standard AI/ML libraries (e.g., PyTorch, TensorFlow). Familiarity with machine learning libraries or frameworks such as PyTorch, TensorFlow, experience with image analysis, especially in a biomedical context or even exposure to bioinformatics tools or pipelines would be a plus.
This role requires a robust technical background, excellent communication skills, and the ability to bridge the gap between business need, legal requirements and technical solutions in the context of AI and natural language processing (NLP) technologies.. Stay current with the latest advancements in LLMs, NLP, Deep Learning and ML research, implementing cutting edge techniques and incorporating them into production systems as appropriate. Juris Doctorate (J.D.) a substantial plus. 2+ years of experience in a technical role, such as data science, machine learning engineering, solutions architect or software development (a focus on AI and NLP preferred). Fully Remote: The estimated base salary range for this position is $120,000 to $170,000.
Fully remote work-from-home flexibility. Database development experience with Hadoop or BigQuery. Familiarity with BI tools such as Tableau, Power BI, Looker. Big Data development experience with Spark, Databricks, Impala, Kafka (preferred). Exposure to machine learning, data science, AI, statistics, or applied mathematics
Our teams apply business intuition along with a diverse set of methods and algorithms, including but not limited to, statistical inference, machine learning, text mining, process mining, network analysis, and data visualization to improve operations.. We are seeking a Senior Data Scientist/Data Science Manager who will help us lead the way in solving critical business problems and derive valuable insights for our customers.. Demonstrated proficiency in Python, SQL in a professional environment; experience with Java or Kotlin a plus. Skills in data cleaning, natural language processing, machine learning, time series, forecasting, visualization, network analysis, and distributed computing. Ability and willingness to travel from time to time (domestic and international); travel expected to be no more than 10% of time