Data Science & Machine Learning Jobs

12 + years of hands-on technical experience in software engineering, with at least 5 + years in a leadership role managing cross-functional teams, including GenAI , machine learning , and cloud infrastructure. Machine Learning & AI : Extensive experience in building and deploying ML models using TensorFlow , PyTorch , scikit-learn , and spaCy , with hands-on experience in integrating them into GenAI applications. Hands on experience in GCP/Data Engineering/DevOps. The AI architect will play a pivotal role in architecting, leading, and actively contributing to the development of GenAI applications, machine learning models, data engineering pipelines, and cloud-native infrastructure. This hands-on leadership position requires extensive technical expertise and experience in managing a diverse, cross-functional team of engineers spanning GenAI App Development, Data Science, Machine Learning, Full Stack, DevOps, Cloud Infrastructure, and API development.

Inuvo is seeking a highly skilled and motivated Machine Learning Engineer / Data Scientist to join our team.. Drive innovation by exploring and applying cutting-edge machine learning and data science methodologies.. Minimum 3 years of experience in machine learning, data science, algorithm design, and large-scale statistical analysis.. Proficiency in large-scale data processing tools such as Spark or Hadoop.. Experience with Large Language Models (LLMs) and Natural Language Processing (NLP) is highly desirable.

As a Machine Learning Engineer, you will play a prominent role in developing generative AI/ML models for multi-modal, multi scale biology. Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;.. Masters or Ph. D. degree in a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience;.. Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX;.. Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging;

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Within the monetization ML team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners, while respecting users' privacy choices. Experience in privacy preserving machine learning techniquesDeep practical knowledge of large scale recommender systems, or ads deliver funnelsExperience in deep learning, transformers, deep cross network, etc. Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow. Experience with large scale data processing (e.g. Hive, Scalding, Spark, Hadoop, Map-reduce).

As a Staff Machine Learning Engineer, you will design, develop, and scale advanced ML models to enhance these signals, ensuring they are accurate, reliable, and optimized for Uber's dynamic marketplace. Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc. Work with real-time streaming data and large-scale distributed systems to ensure Uber's signals are up-to-date and responsive to market dynamics. 6+ years of experience in machine learning, applied data science, or AI-driven optimization in large-scale systems. Strong ML expertise, including experience with time-series forecasting, predictive modeling, and real-time inference.

The Risk Data Science team is looking for a Sr Staff Data Scientist to develop advanced machine learning models, guide measurement, strategy, and data-driven decision making to support various credit risk areas at SoFi. The Sr Staff Data Scientist will work closely with Credit Risk, Product, Engineering teams to design solutions for loss mitigation and loss forecasting. Proactively identify opportunities and collaborate cross functionally to develop, implement, and continuously improve machine learning models and strategies that support various credit and operational procedures for loss mitigation and loss forecasting.. Collaborate with Model Risk Management team and Fair Lending team to demonstrate models are developed with high level rigor that satisfy Model Risk Management requirements, Fair Lending requirements, and other regulatory requirements.. 8+ years of work experience in the related areas especially loss mitigation and loss forecasting with a Master’s or PhD degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or a quantitative field. These methods include (but not limited to) regression, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications.

This role blends data science with cyber forensics to build ML models that power proactive and autonomous threat prevention systems. Design and optimize machine learning algorithms for behavior-based threat identification, anomaly detection, and malware classification. Hands-on experience with security telemetry tools including SIEMs, EDRs, PCAPs, syslogs, and sandbox data analysis. Proficiency in Python, ML frameworks like PyTorch or TensorFlow, and data processing libraries (e.g., Pandas, Spark). Understanding of TTPs, threat actor behaviors, and the MITRE ATT&CK framework.

As an ML Engineer: Memory, you'll take on a high priority/visibility and largely unsolved problem: designing and implementing a scalable approach to personalizing LLM outputs based on a user’s past interactions.. Develop a system for compacting, storing, and retrieving bots’ “memories” to enhance real-time LLM inference.. Exceptional programming skills in Go (preferred), Rust, Python, C. Proficiency with deep learning and NLP frameworks like Scikit-learn, PyTorch, TensorFlow, etc.. WFH equipment provided for full-time hybrid/remote employees.

We have an opportunity available for a Data Scientist to work in the field of cells, genomics and related areas. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Senior Scientist I, Data Science: $229,000 - $313,950.. Senior Scientist I, Data Science: $212,000 - $292,100

Machine Learning Engineer - Product Marketing Customer Analytics. The Product Marketing Customer Analytics team is seeking a Machine Learning Engineer with deep technical experience in predictive analytics and analytic engineering.. Manage ML projects through all phases, including data quality, algorithm/feature development, predictive modeling, visualization, and deployment and maintenance.. Comfortable with advanced deep learning frameworks (Tensorflow, PyTorch) and adept at designing and scaling ML platforms that include feature stores, automated retraining pipelines and CI/CD integration.. Solid technical database and data modeling knowledge (Oracle, Hadoop, SnowFlake), and experience optimizing SQL queries on large dataset for performance-critical analytics.

The Enterprise People Analytics team at Chewy is building advanced AI and machine learning solutions to redefine HR decision-making. As a Machine Learning Engineer (MLE) focused on AI product development, you will design and deploy innovative machine learning models, mentor junior Team Members, and drive the production of scalable AI solutions that empower Chewy’s HR function. Unstructured Data Analysis: Lead research projects involving unstructured data, including natural language processing (NLP), dynamic graph data, and LLM-backed text analytics to uncover actionable insights. Technical Expertise: Sophisticated knowledge of machine learning, statistical modeling, and AI methodologies, with hands-on experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). We offer parental leave, family services benefits, backup dependent care, flexible spending accounts, telemedicine, pet adoption reimbursement, employee assistance program, and many discounts including 10% off pet insurance and 20% off at Chewy.com.

Maxar is seeking a talented and driven Machine Learning Engineer to join our innovative team.. Contribute to the development of best practices and standards for machine learning development and deployment.. Solid understanding of machine learning concepts, algorithms, and libraries (e.g., scikit-learn, TensorFlow, PyTorch).. Experience with data manipulation and analysis using tools like Pandas and NumPy. Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP).. Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning.

Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making. Train, validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and tools. 4+ years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization. Experience with one or more Advanced Data Science software languages (R, Python, Scala, SAS). Experience with Google Analytics, Adobe Analytics, Optimizely a plus

Familiarity or experience with developing solutions in response to U.S. Government Agencies’ solicitations, to include but not limited to the following: Department of Transportation (e.g., FAA), NASA (including JPL), Department of Commerce (e.g., NOAA), Department of Energy (e.g., HQ, NNSA), or National Science Foundation.. Programming:Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala.. Deep Learning: Understanding neural networks, backpropagation, architectures like CNNs, RNNs, transformers, and tools like TensorFlow, PyTorch, or Keras.. Big Data Technologies:Distributed Computing: Tools like Apache Spark, Hadoop.. Software Engineering & DevOps:Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI.Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.

Machine Learning Engineer (Federal AI & Predictive Analytics). Blueprint Creative Group is seeking a Machine Learning Engineer with a strong background in AI-driven predictive analytics and federal cybersecurity applications.. Implement and fine-tune deep learning frameworks such as TensorFlow, PyTorch, and Scikit-Learn. Ensure AI compliance with FedRAMP, Zero Trust, NIST AI ethics, and CISA cybersecurity guidelines. Strong programming skills in Python, R, and SQL; familiarity with cloud AI tools like AWS SageMaker, Azure AI, or Google Vertex AI

This is an amazing opportunity for candidates who are passionate about leveraging their expertise in machine learning and artificial intelligence to drive innovation in the fintech domain.. As the Lead Data Scientist, you will have the chance to work with cutting-edge technologies and vast amounts of data to develop impactful solutions that shape the future of the banking industry.. - Stay up-to-date with the latest advancements in data science and fintech to continuously enhance analytical capabilities. - Experience with big data processing frameworks like Apache Spark or Hadoop. - Proficient in data visualization tools, such as Tableau or Power BI

We're looking for an outstanding Big Data HadoopEngineer to provide vision, gather requirements and translate client userrequirements into technical architecture and design and implement an integratedBig Data platform and analytics solution.. ·Strong project experience with AmazonEMR/Databricks/Cloudera CDP is must.. ·4-5 experience building data pipelines usingHadoop components Sqoop, Hive, Solr, MR, Impala, Spark, Spark SQL., HBase.. ·4-5 years of programming experience inPython, Java and Scala is must.. A reasonable, good faith estimate of the minimum and maximum forthis position is $73 to $77.

Machine Learning Engineer - AI Search. Zoom is looking for an innovative and skilled Machine Learning Engineer to join our Search team.. Have 4+ of hands-on experience in machine learning, particularly within search, ranking, information retrieval, or natural language processing (NLP). Have experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or similar.. Our structured hybrid approach is centered around our offices and remote work environments.

Develop new advanced algorithms using, machine learning techniques, deep learning models, digital signal processing techniques, optimization and numerical modeling in MATLAB, Python or similar software.. Responsible for algorithm design, development, implementation, testing, and documentation for Biomedical Signal Processing systems.. At least 6+ years of experience in AI/ML, statistical signal processing, and deep learning techniques, optimization methods, and numerical modeling.. Algorithm development experience using machine learning techniques such as regression, classification, clustering, etc., and deep learning techniques using neural networks, CNN, RNN, etc.. Familiarity with DSP architecture and embedded systems.

As a core member of the NLP team, you will research, prototype, develop, deploy and scale innovative Machine Learning/Deep Learning solutions in collaboration with Linguistic Experts and Product Management teams.. You will develop predictive models on large-scale datasets to address various business problems leveraging advanced statistical modeling, machine learning, deep learning or data mining techniques.. 5+ Years of experience with building end-to-end systems based on machine learning or deep learning methods (ETL, modeling and deployment).. Experience with deep learning-based NLP models such as BERT, GPT, other transformers.. Experience with machine learning techniques, tools, and frameworks like Keras, TensorFlow, pytorch