Data Science & Machine Learning Jobs

We are seeking an experienced Artificial Intelligence (AI) Tester to join our team. Skilled in AI development frameworks such as TensorFlow, PyTorch, scikit-learn, and/or Keras.. Understanding of and experience in machine learning and artificial intelligence testing.. Paid Time Off, Paid Holidays, Paid Leave (e.g., Maternity, Paternity, Jury Duty, Bereavement, Military).. Corporate Fellowship: Opportunities to participate in company sports teams and employee-led interest groups for personal and professional development.

In addition, the candidate will leverage their expertise in statistical analysis, machine learning and data visualization.. Bachelor's degree inData Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.. Strong proficiency in programming languages commonly used in data science such as Python, R, and SQL.. Extensive experience with machine learning frameworks (e.g., scikit-learn, TensorFlow,PyTorch) and advanced statistics.. Proficient in data visualization and business intelligence tools (e.g., Tableau, Power BI).

SilverEdge is a premier provider of innovative cyber, software and intelligence solutions addressing everyday challenges to meet mission goals across the DOD and Intel Communities and beyond.. We are seeking a candidate to write software using machine learning tools to analyze signals, identify waveforms and create new waveforms for communication systems.. 6+ months experience with Machine Learning toolset. Experience with one or more machine learning toolsets Tensorflow, Pytorch, Scikit-learn, Apache Mahout or others.. Convert prototype investigation into scalable operational systems

Working on problems of moderate scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.. Develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques.. Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or a related technical field.. and Java, or experience with scripting languages such as Python, Perl, PHP, or shell scripts.. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Big Data, dataflows, Artificial Intelligence / Machine Learning (AI/ML) familiarity, Analytics in GME, Jupyter notebooks, and Spark. Degree in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity. Employ some combination (2 or more) of the following areas: Foundations (Mathematical, Computational, Statistical); Data Processing (Data management and curation, data description and visualization, workflow, and reproducibility); Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations). Unlimited access to Red Hat Enterprise Linux, AWS, and NetApp training and accreditation

We're looking for a Lead Data Scientist with deep technical expertise and strong communication skills to lead end-to-end AI/ML projects for top-tier clients across marketing, customer experience, and business process optimization and operations. Design and oversee robust data pipelines using SQL, Spark, and cloud platforms (AWS, GCP, Azure). Architect and implement solutions involving LLMs, transformer-based models, and AI agents for generative tasks and automation. Proficiency in Python (and optionally R or Scala), including libraries like scikit-learn, TensorFlow, PyTorch. Strong SQL and data engineering skills; Spark/Databricks experience is a plus.

Lead Machine Learning Engineer (ML Algorithms, Deep Learning, Python, AWS). As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.. At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).. McLean, VA: $193,400 - $220,700 for Lead Machine Learning EngineerNew York, NY: $211,000 - $240,800 for Lead Machine Learning EngineerRichmond, VA: $175,800 - $200,700 for Lead Machine Learning EngineerSan Francisco, CA: $211,000 - $240,800 for Lead Machine Learning Engineer. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

Design and maintain fraud rules and scoring logic for transaction monitoring systems. Ensure alignment with regulatory expectations, model risk governance, and internal audit requirements. Explore and implement new technologies (e.g., graph analytics, behavioral biometrics, NLP) for advanced fraud detection. Strong command of Python, R, SQL, and data science libraries (pandas, scikit-learn, TensorFlow, etc.. Exposure to real-time fraud systems (e.g., SAS Fraud Management, Actimize, Falcon, etc.)

🚀 Publish, present, and patent high-impact findings in AI and machine learning.. Conduct cutting-edge research in artificial intelligence, including areas such as natural language processing, computer vision, generative models, and reinforcement learning.. Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ACL, CVPR, ICLR) is highly preferred.. Expertise in machine learning, deep learning, or statistical modeling.. Experience with model development using TensorFlow, PyTorch, JAX, or similar frameworks

Collaborate across backend, frontend, and data teams to integrate AI agents, multi-agent orchestration workflows, and MCP-compliant tools into PRIMA’s Control Tower and runtime environments.. Design and implement cloud-native pipelines and infrastructure using IaC and DevSecOps principles. Strong experience with AI/ML libraries such as scikit-learn, SparkML, TensorFlow, PyTorch. Experience with Docker, Kubernetes, and container-based deployment. Strong experience with data mining, supervised, and unsupervised learning methodologies including data dimensionality reduction, correlation analysis, linear regression, PCA, clustering, random forest, etc.

Join our team as an experienced Senior Data Scientist to extract valuable insights from complex datasets and apply advanced analytical and machine learning techniques to solve critical business problems within an AI tech company context.. You will be responsible for the full data science lifecycle, from data collection and cleaning to model development, deployment, and interpretation.. Minimum 6 years of experience in data science, statistical analysis, or machine learning.. Proficiency in programming languages such as Python or R, and extensive experience with data science libraries and frameworks (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).. Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is often preferred for senior roles.

We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation.. Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.. Have proficiency in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.. The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation’s most critical defense, security, space and science challenges.. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development.

Syntes AI, Inc. is the creator of the Syntes AI software platform—a cloud-based solution for Multi-Domain Data Management and Data Analytics using Artificial Intelligence and Machine Learning technologies.. Bachelor’s or Master’s degree in Applied Mathematics, Computer Science, Artificial Intelligence, Machine Learning, or a related field.. Solid understanding of mathematical and data processing techniques: linear algebra, graph theory, vector and matrix calculations, probability theory, and statistical analysis; advanced Excel skills for data analysis.. Knowledge of machine learning concepts and algorithms: knowledge representation, problem-solving, uncertain logic, neural networks, natural language processing, deep learning, reinforcement learning, large language models, and generative models.. Knowledge of containerization and orchestration technologies like Docker and Kubernetes.

Artificial Intelligence & Natural Language Processing Research Scientist Join to apply for the Artificial Intelligence & Natural Language Processing Research Scientist role at Howard University.. Howard University is seeking a Research Scientist to lead innovative projects in AI and NLP, mentor emerging talent, and advance technology in these fields.. Design and validate NLP techniques, contributing innovative solutions to the field.. Willingness to travel and obtain/maintain US Top Secret/SCI security clearance.. Expertise in ML frameworks (TensorFlow, PyTorch) and data formats (JSON, XML).

Mission focus is on developing next-gen tools for detecting cyber-attacks, enhancing network resilience, and improving small-form factor sensor systems while maintaining a focus on cutting-edge technologies like machine learning and software-defined networking. Conducting Radio Frequency (RF) machine learning research or developing signal processing algorithms for wireless systems.. Interest and/or experience in one or more of the following domains: digital signal processing, RF software engineering, algorithm development, software defined radio, and machine learning.. Experience with modern machine learning development frameworks and platforms (e.g. Keras, TensorFlow, PyTorch) is expected.. Familiarity with multiple-antenna or distributed signal processing techniques

We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation.. Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.. Have proficiency in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI. The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation’s most critical defense, security, space and science challenges.. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development.

Expertise in Python and R with advanced knowledge of relevant libraries (e.g., Pandas, Scikit-learn, TensorFlow, Keras, etc. We are seeking a skilled and experienced Data Scientist / Artificial Intelligence / Machine Learning Engineer to join our team.. AI Technologies: Develop solutions using AI technologies such as deep learning, natural language processing (NLP), and computer vision.. Programming & Tool Expertise: Use Python, R, and other programming languages to manipulate data and build scalable, efficient models and analytics pipelines.. Leverage industry-standard libraries (e.g., TensorFlow, PyTorch, Scikit-learn) for machine learning and data manipulation.

AI/Machine Learning Engineer, Manager Consultant. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape.. Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.. Skills in data visualization and storytelling with data.. Tagged as: Big Data , Data Visualization , Industry , Natural Language Processing , NLP , United States

NET, LINQ, gRPC), communication protocols (e.g., WS-Biometric Devices, RTP/RTSP, WebRTC, HTTPS Live Streaming), and database systems (e.g., Oracle, MySQL, PostgreSQL, MongoDB, Elasticsearch). Experienced in working with web services (RESTful and SOAP APIs), cloud platforms (e.g., AWS, Azure, GCS), and network infrastructure (e.g., routers, switches, web/database/mail/DNS/proxy servers, IDS/IPS, firewalls, DMZs). Familiar with modern product development practices and tools, including Kubernetes, Docker, Git, Jira, Agile methodologies, DevOps, and CI/CD pipelines. Knowledgeable in machine learning and deep learning development, including the use of frameworks such as TensorFlow, PyTorch, and Keras. Familiarity with machine and deep learning development practices, frameworks/libraries (e.g. TensorFlow, PyTorch, Keras), employment, computing requirements and limitations when applied to computer vision, big data analysis and other complex tasks demanding Artificial Intelligence-like capabilities.

Artificial Intelligence/Machine Learning Engineer, Lead. As a machine learning engineer on our mission-driven team, you’ll train, test, deploy, and maintain models that learn from data.. Knowledge of foundational concepts of application development, infrastructure management, data engineering, and data governance. Master's degree in advanced math, artificial intelligence, data science, computer science, or deep learning and 10+ years of experience deploying machine learning algorithms, or Bachelor's degree in these fields with 17+ years of experience deploying machine learning algorithms. Ph. D. in advanced math, artificial intelligence, data science, computer science, or deep learning