Data Science & Machine Learning Jobs

Strong experience manipulating data set and building statistical models, has master’s or Ph. D. in statistics, mathematics with focus on ML, NLP, machine learning or another quantitative field.. Strong Knowledge and experience in statistical and data mining techniques – GLM/regression, Random Forest, Boosting, text and data mining.. Experience querying database and using statistical computer languages : R , Python, SQL etc.. Exp leveraging big data and search technologies (e.g., Spark, Elastic Search, Natural Language Processing, Web Crawling).. Knowledge of machine learning techniques and algorithms and be able to apply them in data driven natural language processing techniques.

Our comprehensive audience engagement platform includes creative strategy and execution. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC. As an Applied Scientist, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). Develop and deploy machine learning models at scale to address key challenges in programmatic advertising, such as user response prediction, bid landscape forecasting, and fraud detection. Experience with Python and libraries like Scikit-Learn, TensorFlow/PyTorch.

Developing new computer vision algorithms with founders in C/C. Exposure to new Deep Learning techniques for image recognition. MS/PhD degree or equivalent practical experience in Computer Science, AI, Machine Learning, or related technical field. Knowledge and experience in application of Deep Learning to Computer Vision problems. Pet insurance for your fur babies

As part of our Global Data Insight & Analytics (GDI&A) team, you'll play a pivotal role.. Ford's GDI&A department is on the hunt for talented individuals skilled in Machine Learning, Big Data, Statistics, Econometrics, and Optimization.. Expertise in one or more core domains involved in machine learning model deployment, including data engineering, model building, MLOps. Natural Language Processing (finetuning and distillation of LLMs, evaluation of LLM-powered applications, deploying models at scale). Physics-informed neural networks (ML for computational fluid dynamics or finite element analysis, point cloud or mesh-based neural networks, PDE surrogate modelling)

Machine Learning Engineer.. As a Machine Learning Engineer on our GenAI Engineering team, you will play a critical role in shaping the future of Zoom AI through innovative engineering solutions. or CUDA, with experience in building scalable software systems. Understand deep learning frameworks such as PyTorch, TensorFlow, or similar. Our structured hybrid approach is centered around our offices and remote work environments.

Strong programming skills in Python, GoLang with experience in other languages such as Java, C. Experience with ML frameworks such as TensorFlow, PyTorch, and/or scikit-learn. Familiarity with containerization and orchestration tools like Docker and Kubernetes. Knowledge of infrastructure-as-code tools such as AWS CDK and Cloudformation. Familiarity with data engineering tools such as AWS EMR, Glue and Apache Spark.

NVIDIA is seeking an experienced Machine Learning Engineer to join its Autonomous Vehicle team.. In this role, you will develop key features for our autonomous driving platform by applying machine learning to prediction, planning, and control problems.. Collaboration across teams and disciplines such as computer vision, computer graphics, and machine learning is encouraged.. Research, implement, and evaluate deep-learning-based methods for prediction and planning in NVIDIA's Autonomous Vehicle products.. At NVIDIA, we are powering a revolution in AI with deep learning techniques on NVIDIA GPUs, enabling breakthroughs in image classification, speech recognition, NLP, and autonomous vehicles.

We are looking for applicants interested in computer vision, natural language processing, machine learning, robotics, agents, and/or embodied AI. International candidates are welcome to apply.. AI for Common Good: Apply AI to help address global challenges such as climate change, illegal fishing, and wildlife poaching.. We regularly publish in high-profile conferences and journals in computer vision (CVPR, ICCV, ECCV), robotics (CoRL, RSS, IROS, ICRA), machine learning (e.g., NeurIPS, ICLR), NLP (e.g., ACL, EMNLP), among others.. A strong foundation (typically PhD level) in one or more of the following areas: computer vision, machine learning, (M-)LLMs, foundation models, robotics, embodied AI, natural language processing, knowledge representation and reasoning, and agents.. Experience with deep learning frameworks (e.g. PyTorch, Tensorflow, Jax).

We are also using the latest generative AI technologies to re-imagine product experiences, and are developing AI Assistants both for our customers and to make Stripes more productive across Support, Marketing, Sales, and Engineering roles within the company. Credit Detection brings together machine learning with product development to lower Stripe’s credit risk at scale, while retaining a best in class user experience. As a machine learning engineer, you will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. Experiment and iterate on ML models (using tools such as PyTorch, TensorFlow, and XGBoost) to achieve key business goals and drive efficiency.. Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark

As a Principal Scientist Machine Learning, you will be responsible for developing the frameworks and core models that propel our antibody design process forward.. Deliver robust, production-quality models that will drive the next generation of antibody design, advancing both engineering and de novo. A PhD in biochemistry, biophysics, computational chemistry, computational biology, computer science, machine learning, or a related discipline solving biological or chemical problems using computational approaches.. Strong background and demonstrated experience in machine learning/deep learning, modeling, simulation, and design, particularly in sequence and structure-based antibody design.. Demonstrated experience in the Python programming language in addition to standard machine learning tools (PyTorch, TensorFlow, JAX, PyG, PyMC, etc).

We’re a small, high-impact team based in Seattle focused on applying advanced AI to complex, often unconventional challenges.. Our work spans autonomous systems, predictive infrastructure, synthetic biology, and defense-grade automation.. If it’s ambitious, technical, and hasn’t been done before, we’re probably already working on it.. What You’ll DoAs a Neural Network Specialist, you’ll be responsible for designing and optimizing deep learning architectures that push the limits of what’s technically possible.. You’ll collaborate closely with the CTO and a diverse team of engineers, scientists, and domain experts to move ideas from prototypes to deployment.

The Data Scientist will play a key role in designing and implementing advanced analytics solutions, employing statistical modeling, machine learning, and data visualization techniques.. A Data Scientist is responsible for extracting actionable insights from large and complex datasets using advanced analytical techniques, statistical modeling, and machine learning algorithms.. · Design and implement machine learning algorithms for predictive modeling, classification, and clustering.. · Utilize tools such as Tableau, Power BI, or custom visualization libraries.. · Experience with machine learning frameworks and libraries (e.g., TensorFlow, Scikit-Learn).

Language: Python, PySpark, SQL (advanced), Scala (nice to have)Database: Relational (Oracle, Postgres,e tc.). , NoSQL (MongoDB, Cassandra.. Etc)Tools: Spark, Databricks, Hadoop, Kafka, Airflow, Apache NiFi (any 2 – 3)Cloud Platforms: AWS, or Azure or GCPReporting Tools: PowerBI, Tableau, Etc. Others: CICD, Git, Data Pipelines, Performance Optimization, etc.. AI / ML: Must be trained in AI Augmented development using Copilot & Other LLMs. Should be comfortable adopting GenAI in all phase of SDLC.Advanced troubleshooting skills & Experience with logging and monitoring tools like Kibana to trace logs of microservices/APIs for interactions between external systems.. Developer leadAWS Airflow, Apache Airflow,Azure Databricks,BPM,Microsoft Azure Databricks,Python,SQL,Spark,business administration,business organization,data analysis,data processing,data querying,data science,data science solutions,information technology,management,programming,software development,technology,web application,web application frameworks,web applications development, workflow management system

As a Principal Scientist Machine Learning, you will be responsible for developing the frameworks and core models that propel our antibody design process forward. Deliver robust, production-quality models that will drive the next generation of antibody design, advancing both engineering and de novo.. A PhD in biochemistry, biophysics, computational chemistry, computational biology, computer science, machine learning, or a related discipline solving biological or chemical problems using computational approaches. Strong background and demonstrated experience in machine learning/deep learning, modeling, simulation, and design, particularly in sequence and structure-based antibody design. Demonstrated experience in the Python programming language in addition to standard machine learning tools (PyTorch, TensorFlow , JAX, PyG, PyMC, etc).

Experience with RAG AI: Machine Learning Deep Learning Scikit Spark ML TensorFlow Keras NLP spacy nltk. Experience with AWS SageMaker Ray Distributed systems / Big Data: Spark Kafka Hadoop HBase Cassandra. Experience with Data Science: Python data analytics ecosystem Pandas Scikit etc.. Experience with Datastores: Vector stores MongoDB Atlas Milvus NoSQLs HBase Cassandra MongoDB Redis and SQLs Postgres. Experience working on MySQL DevOps / Tools: Docker Kubernetes Ansible Terraform Linux git Experience in building scalable distributed systems Monitoring and performance tuning of Python / Java apps Experience with Databases and distributed systems Experience in leading / mentoring focused teams to achieve excellent outcomes

Data Scientist - Spear AILocation: On-site, Washington, DCClearance Required: TS/SCI (active)Employment Type: Full-time, salaried, benefits-eligibleAbout Spear AI:Spear AI delivers cutting-edge artificial intelligence solutions tailored specifically for maritime defense and national security operations.. Leveraging advanced data management, AI-driven decision intelligence software, and innovative sensor technologies, Spear AI provides mission-critical capabilities to government, defense, and intelligence customers.. Founded by maritime and technology experts with extensive operational experience, Spear AI is positioned to be a leading provider of scalable, integrated AI solutions for defense. the Role:Spear AI seeks a Data Scientist to advance applied machine learning and analytics within the an AI Task Force.. Proficiency in Python and core data science tools (NumPy, pandas, scikit-learn, PyTorch/TensorFlow).

Summary of Position:Entry-Level Innovation AI Developers are responsible for assisting in the creation, deployment, and maintenance of artificial intelligence solutions.. They support senior developers in building and integrating AI models into applications and systems, including natural language processing (NLP), computer vision, and predictive analytics.. Essential Functions:•Collect, clean, preprocess, and analyze datasets for AI model training, validation, and testing•Write, test, and debug code related to AI model training, deployment, and integration into applications and systems•Apply programming knowledge and computer science principles to support AI system architecture and solution design •Collaborate with team members to integrate trained AI models (e.g., NLP, computer vision, predictive models) into production-level applications.. Additionally, employees may be expected to help set up customer demos in the innovation lab using equipment such as industrial PCs (IPCs), Human Machine Interfaces (HMIs), cameras, sensors, lighting, robots, and other relevant technology.. Required Education and Experience:Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field required.

In the role of AI (Artificial intelligence) Software Engineer Intern you'll play a pivotal part on our Engineering team.. The Engineering Intern will assist the senior engineers in the designing, building, and deploying machine learning (ML) models and AI solutions.. Experience with machine learning, deep learning, NLP, and computer vision. Machine Learning Frameworks: TensorFlow, Keras, scikit-learn, PyTorch. Safran Cabin designs, certifies, manufactures and supports innovative aircraft cabin interiors, equipment and systems, providing airlines and OEM Customers with distinctive aircraft branding, and their passengers with a safe, comfortable and enjoyable flying experience.

We at Innovaccer are looking for a Staff Engineer specializing in Artificial Intelligence (AI) who leads the design, development, and deployment of advanced AI systems.. Experience with natural language processing (NLP), computer vision (CV), or other specialized AI domains. Experience with big data tools (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud). Senior / Staff Software Engineer - Computational Chemistry / Molecular Dynamics Senior Frontend Engineer, Crypto, Credit Card & SoFi Money San Francisco, CA $128,000.00-$240,000.00 2 weeks ago. Senior IT Support Engineer (Onsite/Hybrid) - San Francisco (Peninsula) San Lorenzo, CA $5,496.00-$7,007.00 2 weeks ago

We are looking for applicants interested in computer vision, natural language processing, machine learning, robotics, agents, and/or embodied AI. International candidates are welcome to apply. AI for Common Good - Apply AI to help address global challenges such as climate change, illegal fishing, and wildlife poaching.. We regularly publish in high-profile conferences and journals in computer vision (CVPR, ICCV, ECCV), robotics (CoRL, RSS, IROS, ICRA), machine learning (e.g., NeurIPS, ICLR), NLP (e.g., ACL, EMNLP), amongst other areas. A strong foundation (typically PhD level) in one or more of the following areas: computer vision, machine learning, (M-)LLMs, foundation models, robotics, embodied AI, natural language processing, knowledge representation and reasoning, and agents. Experience with deep learning frameworks (e.g. PyTorch, Tensorflow, Jax).