Data Science & Machine Learning Jobs

Develop and fine-tune CNNs, SSM, and other deep learning models to enhance image processing in pharmaceutical applications.. Optimize LLM and CV frameworks for efficiency and scalability.. Skills: Computer Vision, CNNs, SSM, and Generative AI, LLMs, multi-modal AI systems, Linux, Python, AWS & Machine Learning.. Education: MSc or PhD in Data Science, Machine Learning, AI, or a related field.. US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions.

Join to apply for the Staff Machine Learning Engineer, Level 6 role at Snap Inc. We’re looking for a Staff Machine Learning Engineer to join Snap Inc!. Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks.. Machine Learning Engineer - New Verticals - Search & Recommendations.. Software Engineer Graduate (TikTok Short Video) - 2025 Start (Bachelors/Master)

Join to apply for the Machine Learning Engineer, Level 4 role at Snap Inc. Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks. Sign in to set job alerts for “Machine Learning Engineer” roles.. Software Engineer, Game Support, Game Studio Santa Monica, CA $178,000.00-$313,000.00 1 week ago. Senior Machine Learning Engineer - AI Solutions Santa Monica, CA $100,800.00-$161,000.00 2 weeks ago

Hulu. ESPN. ABC. ABC News. Disney Entertainment and ESPN Product & Technology team is looking for a passionate Lead Machine Learning Engineer to drive the security and operation anomaly detection initiatives within the Commerce, Data, and Identity Alliance.. Proficiency in Python, R, SQL, and other relevant programming languages.. Experience with data wrangling tools (e.g., Pandas, NumPy), databases (e.g., MySQL, PostgreSQL), and big data platforms (e.g., Spark, Databricks, Jupyter, Snowflake, Airflow, GitHub).. Broadcast Media Production and Distribution

They should also have experience in developing Big Data pipelines in orchestration tools such as Airflow and Oozie, designing tooling for access management, monitoring, data controls, and self-service ETL/Analytics pipelines.. Other requirements include hands-on experience with On-Prem Big Data Platform, sound knowledge of Distributed Data Processing frameworks, resource management frameworkslike YARN, and proficiency in writing data pipelines using Spark, Python and Scala.. Additionally, the candidate should be able to diagnose software issues and engineering workarounds, have a good understanding of BI tools such as Tableau/Power BI and MicroStrategy for Big Data, and be able to lead, guide and assist team members with project development and problem solving.. Big Data Technologies: Knowledge of Big Data technologies such as Hadoop, Spark, Hive, Pig, Kafka, and NoSQL databases such as MongoDB, Cassandra, and HBase.. Cloudera/Hortonworks/Databricks - Spark/Hadoop certification

We are searching for a Machine Learning Engineer to join our collaborative group that includes a mix of big data, API, and full stack development teams.. 2+ years of professional development experience as Machine Learning Engineer, Data Scientist or related role. Experience with ML cloud tools such as Databricks, Amazon Personalize, Comprehend, SageMaker, and Rekognition.. On-site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes. Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks

Depending on their backgrounds and interests, they may engage in market research, experimentation, forecasting, causal measurement, optimization, or data-related automation and data science product development.. Prototyping data pipelines or tools to automate the creation and/or deployment of knowledge gained from statistical models, machine learning models, or artificial intelligence. Using code and technology to build data pipelines or tools to automate the creation and/or deployment of knowledge gained from statistical models, machine learning models, or artificial intelligence. Monitoring the health and deployment of statistical and machine learning models embedded in data science products. Relevant areas include (but are not limited to) statistics, data science, applied mathematics, operations research, engineering, and computer science

Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more. Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets. Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Familiar with metadata management, data lineage, and principles of data governance. Experience with: AWS, Docker, Airflow, Databricks.

Computer Vision/Machine Learning Engineer Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology.. Anduril’s Tactical Reconnaissance and Strike Division (TRS) is responsible for design and development of Anduril’s fleet of small warfighting and surveillance drones deployed around the world, including Ghost, Anvil, Altius, and Bolt. We work in close coordination with specialist teams like Perception, Autonomy, and Manufacturing to solve some of the hardest problems facing our customers.. We are looking for software engineers and roboticists excited about creating a powerful robotics stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.. Experience with Python development and deep learning frameworks such as PyTorch and TensorFlow. Experience in one or more of the following: Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, RGB-D and LIDAR Sensor Fusion

Hulu. ESPN. ABC. ABC News. Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms.. Disney Entertainment and ESPN Product & Technology team is looking for a passionate Lead Machine Learning Engineer to drive the security and operation anomaly detection initiatives within the Commerce, Data, and Identity Alliance.. Proficiency in Python, R, SQL, and other relevant programming languages.. Experience with data wrangling tools (e.g., Pandas, NumPy), databases (e.g., MySQL, PostgreSQL), and big data platforms (e.g., Spark, Databricks, Jupyter, Snowflake, Airflow, GitHub).

Analytical needs can include: data aggregation / creation, data cleaning / manipulation, commercial data science (e.g., geospatial, machine learning, predictive modelling, NLP, GenAI etc. A minimum of 2 years of experience in applied data science with a solid foundation in machine learning, statistical modeling, and analysis is required for a Data Scientist.. Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.. Technical understanding of machine learning algorithms; experience with deriving insights by performing data science techniques including classification models, clustering analysis, time-series modeling, NLP; technical knowledge of optimization is a plus.. (e.g., Sagemaker, Azure ML, Kubernetes, Airflow)

Requires a minimum of 6 to 7 years of professional Data Science or ML experience; or a Ph. D. degree in operations research, applied statistics, data mining, machine learning, or other quantitative discipline.. Expert in open-source languages such as Python, R, and Julia.. Understanding of statistical methods and advanced modeling techniques (e.g., SVM, K-Means, Random Forest, Boosting, Bayesian inference, natural language processing).. Extensive experience with machine learning and deep learning packages (scikit-learn, XGBoost, Tensorflow or PyTorch).. Experience with LLM fine-tuning and Retrieval-Augmented Generation (RAG) techniques

Anduril’s Tactical Reconnaissance and Strike Division (TRS) is responsible for design and development of Anduril’s fleet of small warfighting and surveillance drones deployed around the world, including Ghost, Anvil, Altius, and Bolt. We work in close coordination with specialist teams like Perception, Autonomy, and Manufacturing to solve some of the hardest problems facing our customers. We are looking for software engineers and roboticists excited about creating a powerful robotics stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications. We are looking for a Computer Vision / Machine Learning Engineer to apply the latest research to solve our toughest problems. Experience with Python development and deep learning frameworks such as PyTorch and TensorFlow.. Experience in one or more of the following:Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, RGB-D and LIDAR Sensor Fusion

Hulu. ESPN. ABC. ABC News. Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. Disney Entertainment and ESPN Product & Technology team is looking for a passionate Lead Machine Learning Engineer to drive the security and operation anomaly detection initiatives within the Commerce, Data, and Identity Alliance. Proficiency in Python, R, SQL, and other relevant programming languages. Experience with data wrangling tools (e.g., Pandas, NumPy), databases (e.g., MySQL, PostgreSQL), and big data platforms (e.g., Spark, Databricks, Jupyter, Snowflake, Airflow, GitHub).

Lead, mentor, and manage a team of machine learning engineers, providing guidance on best practices in ML Ops, infrastructure, and software engineering.. Strong understanding of machine learning frameworks, tools, and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and distributed computing.. Experience with containerization technologies (e.g., Docker, Kubernetes).. Knowledge of big data technologies (e.g., Hadoop, Spark) and data engineering practices.

This leader will be on the ISA leadership team, and will be at the intersection of data, analytics and creative television production and distribution.. The leader will play a pivotal role in scaling the capabilities of the data science expertiseteam inside the larger Insights, Strategy & Analytics team and will unlock value in television production, content distribution & studio financial models.. The successful candidate will have extensive experience in data science methodologies, predictive modeling,machine learning, the latestAI-driven data science innovations, and advanced statistical modeling, with a proven track record of driving business value through data science.. Translate insights into action by delivering models & tools that drive measurable outcomes in key studio production & content distribution areas. Expertisewith data visualization tools such as Tableau or Power BI.

Machine Learning Engineer — Trust and Safety (Account Trust). We are seeking a machine learning engineer who will strive to turn huge amounts of data into actionable insights that improve safe customer experience.. You’ll work with partner teams to develop strategic, long-term fraud prevention solutions while continuously enhancing your software engineering and machine learning expertise.. 3+ years of experience with big data tools (SQL, Spark, Splunk, Python, Jupyter Notebook).. Experience with Python, Scala, Java, or similar, including relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Spark MLlib).

As a Data Science Senior Specialist, your work will help power our planet, reduce carbon emissions and create cleaner air for everyone.. Identifies high-value use cases across business functions and domains to apply artificial intelligence, machine learning and data science to solve previously intractable business problems. Experience using the following database systems: MySQL, PostgreSQL, or MSSQL. Big Data Analytics: Hadoop environment, Hive, Pig or Spark.. Three or more years of experience using machine Learning methods such as deep learning, Bayesian methods, time series analysis, boosting, and bagging.. Two or more years of experience working with GCP, Azure, Snowflake, and PowerBI.

Apply data science methods using Python (or similar libraries) for data cleaning/wrangling, exploratory data analysis (EDA), statistical analysis, and visualization in an Agile development environment. Experience with tools such as R, Python, Tableau, and Power BI. Proficiency in advanced data analytics tools and programming languages such as Python, R, SQL, and experience with AI/ML frameworks like TensorFlow, PyTorch, and Scikit-Learn. Experience leading the development of advanced analytics products and applying data visualization and statistical programming tools to enterprise data to enable key mission outcomes. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark)

The AWS Neuron Compiler team is actively seeking skilled compiler engineers to join our efforts in developing a state-of-the-art deep learning compiler stack.. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI.. - 2+ years of experience developing compiler optimization, graph-theory, hardware bring-up, FPGA placement and routing algorithms, or hardware resource management. - Experience is TensorFlow, PyTorch, and/or JAX. - Experience in LLM, Vision or other deep-learning models