Data Science & Machine Learning Jobs

We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation.. Have at least one year of hands-on experience applying/developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.. Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision ( object detection and visual tracking), multi-agent systems, or optimization/control theory.. 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.

Design, develop, integrate and deploy AI -driven solutions to extract insights from complex, high-volume datasets offering expertise in AI/ML, Large Language Models (LLM), Generative AL, and/or Natural Language Processing (NLP). Apply statistical and deep learning techniques to support predictive modeling, classification, natural language processing, and pattern recognition. Proficiency in Python, R, and/or Java for machine learning, data processing, and algorithm development, with a strong focus on building robust, scalable solutions for operational field deployment.. Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn for building and deploying predictive models.. Bachelor's or Advanced degree or equivalent experience in AI ML (Artificial Intelligence, Machine Learning ), Data Science, Math, or like technical fields

The Senior Data Scientist designs, develops, and implements advanced data science models for priority business use cases across the enterprise.. Define batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment.. Analytical Skills: Strong understanding of core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques.. Data scientist fluent in complex algorithms and analytics methodologies across multiple platforms and languages, including Google Cloud Platform.. Understanding of core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques.

The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve Scale's products and customer experience.. Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment. Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch. Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization. AWS or GCP) and developing machine learning models in a cloud environment

The Essential Skills Every Machine Learning Engineer Should Learn. So what does it take to thrive as a machine learning engineer today?. Fluency with OOP principles like inheritance, encapsulation, and polymorphism enables cleaner system design and code reuse.. Experience with tools like Apache Spark, Kafka, and Hadoop allows for pre-processing large datasets for model training and deployment.. Dean, part of the nomadic human tribe, believes a boat anchored ashore is a tragedy, as it denies the boat its purpose.

Position Summary: The role will lead and mentor a team of data scientists and analysts responsible for delivering machine learning, artificial intelligence, and advanced analytics projects. Minimum 5 years of experience in data science, machine learning, statistical modeling, or optimization in an industry or research setting. Experience with big data technologies such as Hadoop, Spark, and cloud platforms (AWS, GCP, Azure) is a plus. Familiarity with machine learning frameworks, such as TensorFlow, PyTorch, or scikit-learn. Advanced proficiency in Python, SQL, PySpark, or similar analytic tools.

Our team has a mix of highly proficient people from multiple fields such as Machine Learning, Data Science, Software Engineering, Operations, and Big Data Analytics.. Our Senior Researchers tackle such diverse and challenging projects on Image Quality scoring; Automatic Taxonomy Improvement; Entity Resolution of rich, hierarchical Entities; and Conflict Resolution between different representations of the same Entity.. Data Strategy: Partner with the operations and data teams to ensure access to high-quality labeled data, and proactively shape data acquisition strategies where needed.. Deep understanding of modern ML approaches including classification, regression, NLP, clustering, deep learning, and/or reinforcement learning.. Proficiency with big data processing frameworks such as Hadoop, Spark, and SQL.

As a member of our team, youll have the opportunity to work with a team of highly skilled engineers and scientists to bring new experiences to Apple Maps. This position requires a self-motivated engineer/scientist with strong technical and interpersonal skills to handle responsibilities including:We are looking for a Machine Learning Scientist / Engineer who will be converting abstract, high-level goals into concrete, measurable requirements. Deep learning, computer vision, topic modeling, graph algorithms are pluses.. Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Scala, Python, Java, or C. Knowledge of Spark, Apache Hadoop, Solr/Lucene, Cassandra, and related big data technologies.. Masters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.

This individual will partner closely with senior leadership, product, operations, growth, data engineering and data governance teams to operationalize insights, optimize business performance, and expand CAQH’s capabilities in artificial intelligence (AI), machine learning (ML), and decision science. Work closely with Data Engineering, Architecture, and Governance teams to ensure data science solutions are interoperable, secure, and aligned with CAQH’s enterprise data ecosystem. Proficiency in Python, R, SQL, Spark, and data science frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost). Familiarity with data governance and compliance frameworks (e.g., HIPAA, HITRUST, GDPR). Bachelor’s degree in computer science, data science, statistics, applied mathematics, or a related field required.

Strong experience building data pipelines using Hadoop components Sqoop Hive SOLR MR Impala Spark Spark SQL HBase. Strong experience with REST API development using Python frameworks Django Flask, Fast API etc.). Strong experience building data pipelines using Hadoop components Sqoop, Hive, SOLR, MR, Impala, Spark, Spark SQL., HBase.. Strong experience with REST API development using Python frameworks (Django, Flask, Fast API etc.). Director of Talent Acquisition

Machine Learning Model Development: Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.. Required Experience/Knowledge, Skills & Abilities: 3+ years' work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered Knowledge of big data technologies (e.g., Hadoop, Spark Technical Proficiency: Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.. Data Visualization: Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively.. Preferred Experience: Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio etc.). Familiarity with natural language processing (NLP) and computer vision techniques.

As the nation’s largest senior care advisory service, A Place for Mom helps hundreds of thousands of families every year navigate the complexities of finding the right senior care solution for their loved ones across home care, independent living, memory care, assisted living, and more. A Place for Mom is looking for a Staff Machine Learning Engineer to help build practical, data-driven machine learning applications focused in the Engineering space. This position reports to the VP of Engineering and works directly in the Engineering organization while also working closely with the Data Science team which includes data scientists and machine learning engineers. Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applicationsSolve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks. Technical Skills: Expertise in SQL, Databricks, AWS services, Python, Spark and machine learning frameworks such as XGBoost, Scikit, TensorFlow, Keras or PyTorch.

As the nation’s largest senior care advisory service, A Place for Mom helps hundreds of thousands of families every year navigate the complexities of finding the right senior care solution for their loved ones across home care, independent living, memory care, assisted living, and more.. A Place for Mom is looking for a Staff Machine Learning Engineer to help build practical, data-driven machine learning applications focused in the Engineering space.. This position reports to the VP of Engineering and works directly in the Engineering organization while also working closely with the Data Science team which includes data scientists and machine learning engineers.. Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applicationsSolve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.. Technical Skills: Expertise in SQL, Databricks, AWS services, Python, Spark and machine learning frameworks such as XGBoost, Scikit, TensorFlow, Keras or PyTorch.

Come join Intuit as a Staff Machine Learning Engineer!. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).. Knowledge of machine learning techniques (i.e. classification, regression, and clustering).. Understand machine learning principles (training, validation, etc.). Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)

This may involve data exploration, high-performance data processing, and machine learning algorithm exploration.. This may involve speeding up training, making a data processing easier, or data management tooling.. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).. Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).. Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.

+ Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems.. + Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods.. + Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).. + Strong publication record in Natural Language Processing, Machine Learning, Deep Learning or Reinforcement Learning at major conferences or journals.. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We are looking for a Senior Machine Learning Engineer to join the growing AI and Machine Learning team at Strava.. Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, Sagemaker. Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, Snowflake). Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, Go. Were backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and were expanding in order to exceed the needs of our growing community of global athletes.

Job Title: Senior Machine Learning Engineer.. Were hiring a Machine Learning Engineer to join a fast-growing AI startup based in San Francisco , focused on transforming the way sales teams operate. Proficiency in Python, plus experience with libraries like TensorFlow, PyTorch, Keras, scikit-learn.. Strong knowledge of NLP, Deep Learning, Transformers, LLMs. Bachelor's or Masters degree in Computer Science, Machine Learning, Data Science, or related field

We are looking for a Senior Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, Sagemaker.. Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, Snowflake).. Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, Go. Were backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and were expanding in order to exceed the needs of our growing community of global athletes.

You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: computer vision, graph neural network, natural language processing (NLP), inclusive AI, reinforcement learning, user modeling, and recommender systems.. Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems. Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search. MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field. Python) or one ML framework (Tensorflow, Pytorch, MLFlow)