Data Science & Machine Learning Jobs

Key Qualifications BS in Computer Science, Electrical Engineering, Machine Learning, or related technical field. Strong expertise in Python data science stack (NumPy, Pandas) and ML/DL frameworks (scikit-learn, PyTorch, TensorFlow) for end-to-end model development. Solid understanding of software engineering best practices: version control (Git), unit testing, code review, and CI/CD. Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). Preferred Qualifications MS or Ph. D. in Computer Science, Electrical Engineering, Machine Learning or related technical field. Development experience in a cloud service environment such as Amazon AWS, MS Azure, or Google Cloud Platform.

We are looking for a curious, impact-driven early career Data Scientist / Machine Learning Engineer to join our AI R&D team. Model research & prototyping – Explore, implement, and benchmark ML/NLP/generative-AI methods (e.g., LLM fine-tuning, retrieval-augmented generation, document understanding). Education: Ph. D. or M.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a closely related field.. Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, spaCy, or similar. Nice-to-have: exposure to cloud platforms (AWS/GCP), experiment-tracking tools (Weights & Biases, MLflow), or containerized deployment (Docker/Kubernetes).

We are looking for a Senior Machine Learning Engineer, Deployment focused on Deep Learning/Computer Vision. Hands-on, real-world experience with one or more of Computer Vision, Machine Learning, Deep Learning. Hands-on experience on Model Compression techniques such as Quantization, Pruning, Distillation. Proficiency in ML frameworks like PyTorch, Tensorflow, Keras, etc. Experience with one of the following frameworks: Qualcomm SNPE, Tensorflow Lite, CoreML or other similar Edge Inference/NN Acceleration frameworks.

Hulu. ESPN. ABC. ABC News. Our team develops and maintains state-of-the-art recommendation and personalization algorithms that serve hundreds of millions of users across Disney+, Hulu, ABC, and ESPN. As a key member of this team, you will collaborate closely with Engineering, Product, and Data teams to apply advanced machine learning techniques in support of strategic personalization initiatives. Proficiency in at least one of the following deep learning frameworks, tensorflow, pytorch.. Track record of deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark.. Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance

Inkitt is building the Disney of the 21st Century, standing at the forefront of technology and entertainment. Develop and optimize machine learning models for recommendation engines, utilizing techniques such as collaborative filtering, content-based filtering, and deep learning. Contribute to the design and implementation of robust APIs and services, primarily in Python, Go, and TypeScript, to support recommendation features across our apps (Inkitt, Galatea, and GalateaTV). Proficiency in Python and experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with distributed systems and cloud infrastructure, such as AWS, GCP, or Azure.

TS/SCI Machine Learning Engineer. Our client, a 100+ staff, Series C Deep Learning SaaS startup is seeking a ML Engineer with TS/SCI Clearance to deliver best-in-class Predictive Maintenance solutions to the Department of Defense.. Python data science stack (pandas, NumPy, scikit-learn, PyTorch, etc.. Task schedulers (Celery, Airflow, Prefect) & web-app stacks (Flask/Django). Experience in Cyber Analytics, Predictive Maintenance or Supply Chain Optimization would be a nice to have

We are a partnership between two powerhouse organizations-MGM Resorts International and Entain Group. You know our name through our exciting portfolio of brands including BetMGM Sportsbook, Borgata online, Party Casino and Party Poker. Ability to write complex SQL queries and work with large-scale datasets (experience with Snowflake a plus).. Demonstrated experience with statistical analysis, including regression, clustering, predictive modeling, Bayesian methods, and inferential statistics.. Gaming Compliance & Licensing Requirements

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.

As a Machine Learning Engineer, you will contribute to state-of-the-art machine learning infrastructure and relevant software (e.g. supervised learning, reinforcement learning, data management, and evaluation at unparalleled scale).. Address large scale challenges in the machine learning development cycle, especially around distributed training and inferencing environment in the cloud and data engineering.. Project experience working with Pytorch, Tensorflow or other modern deep learning frameworks.. CUDA is a plus, experience with AWS as well.. (Optional) Real-time traffic and autonomous vehicle simulation experience with e.g. Unity, CARLA etc.

Conduct research and experimentation to optimize LLMs, NLP models, and multimodal approaches for healthcare tasks.. PhD in Data Science, Computer Science, Machine Learning, Computational Linguistics, or related fields; or Master's degree combined with equivalent relevant industry experience.. 8+ years of experience applying machine learning and AI to real-world problems, with a focus on NLP and LLMs. Proficiency with Python, SQL, and popular data science libraries such as pandas, NumPy, scikit-learn, and PyTorch.. Proven experience with generative AI and NLP methods, including prompt engineering, embeddings/vector databases, retrieval-augmented generation (RAG), LLM evaluation, and fine-tuning techniques.

We are looking for engineers who want to work on cutting edge technology, that is the intersection of Semantic knowledge bases, agents, NLP, LLM, ML and software engineering.. Come join us to help create a world class team advancing the AI/NLP/ML/LLM/RL/Knowledge Graph technologies.. Proficiency in Python, PyTorch/TensorFlow, Spark, BigQuery. Passion for Large language models, NLP, and Machine Learning at scale. MTV - [Free] Electric Car Charging Station

AEEC is seeking a Principal Artificial Intelligence/Machine Learning Scientist with neural networks deep learning experience who will lead a small team of AI scientists in solving AI problems and advancing AI techniques, science and research agendas of AI in one or more areas.. Ph. D. in a quantitative science: Computer Science, Math, Electrical Engineering, Statistics, or relevant program with major in AI, Machine Learning, or Computational Linguistics. Artificial Intelligence / Machine Learning Research and Development Engineer. Principal Associate, Data Scientist - Shopping AIPrinciple Geospatial Scientist (Data Collection/Quality Manager)Lead Data Scientist & Deputy Program ManagerManaging Consultant Financial Modeler Data ScientistDelivery Consultant – Communications Apps, Data and Machine Learning, WWPS US FederalDelivery Consultant – Communications Apps, Data and Machine Learning, WWPS US FederalArtificial Intelligence/Machine Learning (AI/ML) Engineer. AI Research Scientist: AEC. Remote US or CanadaSenior Healthcare Data Scientist - AI/ML, Stats, OR

The IAD at the University at Buffalo is a leader in advancing AI, data science, and computational research.. IAD fosters innovation by addressing pressing challenges in areas such as education, health care, robotics, and autonomous vehicles, contributing to the future of the U.S. economy and security.. Under the guidance of faculty members, work with and deploy machine learning models (including LLM models) into both on-prem systems and hybrid clouds, ensuring efficient integration into production environments.. 3 years of software engineering (end-to-end full-stack development) and machine learning experience (industry or academia), or an equivalent combination of education and experience Expertise in PyTorch, TensorFlow, distributed ML training, inference, and MLOps tools.. Proficient in AI infrastructure, high-performance computing, cloud platforms ( AWS , GCP ), and parallel programming with GPUs. Knowledge of cloud technologies such as containerization (Docker, Kubernetes) and big data technologies (Hadoop, Spark).

Artificial Intelligence Engineer/Analyst Northern Virginia Full-Time On-site Position Contingent Upon Award Join Synertex and apply your expertise to a mission that matters. RESPONSIBILITIES Design, develop, and deploy AI models using machine learning, NLP, and computer vision to meet mission needs. Proficiency in AI technologies, including machine learning, NLP, and computer vision. PREFERRED QUALIFICATIONS Certifications in AI, machine learning, or data science (e.g., AWS Certified Machine Learning, Google Professional Data Engineer). Knowledge of federal data governance and compliance frameworks (e.g., NIST, FedRAMP).

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

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

Natural language (NLP) models within Generative AI / LLMs. General ML engineering skills and statistical analysis methods, such as classification, association rules, sentiment analysis, topic modeling, time-series analysis, statistical inference, text analytics, data mining and validation methods.. Proficiency in Python for both quantitative analysis and data engineering, and at least one NLP toolkit such as Spacy, OpenNLP, CoreNLP, gensim, NLTK, etc. Familiarity with neural net architectures, and developing models using tools such as Tensorflow or PyTorch.. Familiarity with AWS Connect and Contact Lens

Morgan, Lewis & Bockius LLP, one of the world’s leading global law firms with offices in strategic hubs of commerce, law, and government across North America, Asia, Europe, and the Middle East, is seeking an AI Architect to design, develop, and optimize AI solutions that enhance the firm’s legal services and internal operations.. AI Systems Design: Architect scalable, secure, and high-performance AI solutions tailored to the firm’s needs, including machine learning models, natural language processing tools, and automation systems.. AI Tool Integration: Identify, implement, and integrate third-party AI tools and platforms that can enhance legal operations, improve client services, and streamline internal workflows.. Technical Expertise: Proficiency in AI technologies, including machine learning frameworks (e.g., TensorFlow, PyTorch), natural language processing (NLP), computer vision, and automation tools.. Data Management: Expertise in data management, data engineering, and data security practices to support AI initiatives, including experience with big data platforms and technologies (e.g., Hadoop, Spark).

Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics.. Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.. PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.. Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).. Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.

Client Protection Shared Services – Advanced Analytics is looking for a seasoned and energetic data science leader to join our team as a Lead Data Scientist and help us deliver data science products to the production environment especially for scalable graph analytics. Maintains knowledge of the latest advances in the fields of data science and artificial intelligence to support business analytics.. Expertise handling data across its lifecycle in a variety of formats and storage technologies (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka).. Understanding of advanced machine learning methodologies including neural networks, ensemble learning like XGB, and other techniques.. Artificial Intelligence/Machine Learning