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You'll have the freedom to experiment with and participate in deciding which big data, deep learning and NLP tools are right for Relativity on an ongoing basis.. Communicate across the broader AI team, keeping the team aware of AI platform innovation, learning opportunities, and future areas of innovation.. 2+ years of experience creating resources on AWS, Azure, or GCP using infrastructure as code (e.g., AWS CloudFormation, AWS CDK, Terraform, CDKTF, Pulumi, etc. Experience with Prefect, Airflow, or an analogous workflow tool.. Experience deploying solutions in big data processing frameworks such as Apache Spark, Hadoop, EMR, and Kafka.
At Advana, our engineers ingest data in the platform, unlock secrets, explore new possibilities presented by the IoT, machine learning, and artificial intelligence advances.. They turn complex data sets into valuable information to solve global challenges across private and public sectors — from fraud detection to cancer research to national intelligence — they know, the answers are in the data.. Experience developing data pipelines using Apache Spark, Databricks. Experience with SQL query engines – Databricks, Snowflake and Redshift. Experience with Big Data processing frameworks such as EMR, Athena and Big Query
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.
AI/ML Expertise: Proven experience building and deploying AL/ML models (e.g., regression, classification, NLP, deep learning) using modern frameworks and AWS services like Bedrock and SageMaker. Programming Skills: Proficiency in Python, R, or similar languages widely used in the data science community. Experience with data processing tools (e.g., Pandas, dbt, Airflow). Knowledge of databases (Snowflake, Postgres, DynamoDB) and ETL/ELT processes. As cloud adoption continues to accelerate, so do the complexities and costs associated with it — and macroeconomic conditions only increase pressure to prove cloud efficiency.
The Principal Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. As a Principal Data Scientist, you will lead large data science projects, identifying opportunities to leverage the best technology and approach, and mentoring data scientists on the project team. Expertise running queries against data (preferably with Google BigQuery or SQL).. Expertise in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP. Demonstrated mastery in predictive modeling, data mining and data analysis
You will collaborate with experts in Machine Learning and NLP to advance human language understanding systems. Research, prototype, develop, deploy, and scale innovative Machine Learning/Deep Learning solutions in collaboration with Linguistic Experts and Product Teams. Develop predictive models on large datasets to solve business problems using statistical modeling, machine learning, deep learning, or data mining techniques. 12+ years of professional experience in Deep Learning, NLP, NLG, Question Answering, Text Classification, Information Retrieval, Knowledge Extraction, AI Planning, and Commonsense Reasoning. Experience with deep learning NLP models such as BERT, GPT, transformers.
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
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).
"As an AI Pre-Sales Scientist you'll be responsible for communicating to clients on FICO's AI/Gen AI and machine learning/analytic methods and latest innovations to drive sales efforts for FICO's solutions that manage risk, fight financial crime, build profitable customer relationships, and meet regulatory requirements. As an AI/Gen AI and machine learning/analytic domain expert, you will engage customers at mid-level management and technical levels to ensure strong knowledge of FICO's product differentiation and unique intellectual property (IP). MSc degree incomputer science, engineering, physics, statistics, mathematics, operations research or natural science fieldswith hands-on related experience in data science, including AI/Gen AI and machine learning. Proven and demonstrable experience with at least three of the following machine learning algorithms: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. You'll play a part in our commitment to help businesses use data to improve every choice they make, using advances in artificial intelligence, machine learning, optimization, and much more.
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.
As an Applied Scientist specializing in personalization, lead scoring, and complex modeling, you will tackle cutting-edge challenges in machine learning and deep learning to redefine how our business engages with customers.. Leveraging your expertise in deep learning, NLP, and general modeling, you'll help build solutions that directly influence business outcomes, collaborating with cross-functional teams to turn Client research into scalable, production-grade systems.. Design and deploy predictive lead scoring models to optimize customer acquisition, conversion, and retention strategies using advanced techniques like survival analysis, graph networks, or transformer-based architectures.. Proven success in deploying deep learning models (e.g., BERT/Transformers for NLP, diffusion models, GANs or general DNNs) to solve business problems.. Emerging Techniques: LLM fine-tuning, federated learning, automated feature engineering, siamese networks, backbones (feature extraction networks), efficient transformer architectures.
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.
Job Summary: Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms.. ESPN is building a new real-time video recommendation system as a core capability of our next-generation streaming platform.. We are seeking a Lead Machine Learning Engineer to take ownership of major components of the end-to-end personalization system.. Proficiency with modern ML frameworks such as TensorFlow, PyTorch, or similar.. Strong software engineering skills, with experience in distributed systems, data pipelines, and cloud platforms (AWS, GCP, Azure).
Corner Resources is searching for a Machine Learning Engineer to support the development and deployment of advanced CV models in a production environment.. This role combines deep learning expertise with infrastructure engineering, contributing to scalable ML workflows that power real-world applications.. Duration: -month contract
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.
We are seeking a Lead Machine Learning Engineer to take ownership of major components of the end-to-end personalization system.. Build advanced recommendation models using deep learning, embeddings, sequence models, transformers, and multi-task learning frameworks.. Strong applied ML expertise with experience in personalization, recommendation systems, ranking models, and/or predictive modeling.. Proficiency with modern ML frameworks such as TensorFlow, PyTorch, or similar.. Strong software engineering skills, with experience in distributed systems, data pipelines, and cloud platforms (AWS, GCP, Azure).
Hadoop Admin Ops / SRE role supporting NextGen Platforms built around Big Data Technologies (Hadoop, Spark, Kafka, Impala, Hbase, Docker-Container, Ansible and many more).. Requires experience in cluster management of vendor based Hadoop and Data Science (AI/ML) products like Cloudera, DataRobot, C3, Panopticon, Talend, Trifacta, Selerity, ELK, KPMG Ignite etc.. - Team member will be expected to provide subject matter expertise in managing Hadoop and Data Science Platform operations with focus around Cloudera Hadoop, Jupyter Notebook, Openshift, Docker-Container Cluster Management and Administration. - Expert level knowledge of Cloudera Hadoop components such as HDFS, Sentry, HBase, Kafka, Impala, SOLR, Hue, Spark, Hive, YARN, Zookeeper and Postgres. - Strong technical knowledge: Unix/Linux; Database (Sybase/SQL/Oracle), Java, Python, Perl, Shell scripting, Infrastructure.
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).