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Advanced knowledge of AI frameworks like TensorFlow, Scikit-learn, or PyTorch.. Experience with Databricks, Delta Lake, or Azure-based analytics ecosystems.. Proficiency with BI and visualization tools, such as Power BI, Qlik, Tableau, SQL Server.. Experience in machine learning algorithms, predictive modeling, and anomaly detection.. Conduct in-depth exploratory data analysis (EDA) using Python, SQL, and visualization tools to identify trends, correlations, and data quality issues.
We are looking for a Machine Learning Engineer, LLM to work for our client.. Stay current with the latest research in NLP, deep learning, and generative AI, and apply findings to improve model capabilities.. 3+ years of experience in machine learning or NLP, with a strong focus on deep learning.. Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.. Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
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)
Contrast AI is seeking a highly skilled and innovative Machine Learning Engineer / Data Scientist to join our team. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Hands-on experience with cloud platforms like AWS, GCP, or Azure for deploying machine learning models. Preferred Qualifications Experience with deep learning, reinforcement learning, or natural language processing. Join the Contrast team as a Machine Learning Engineer/Data Scientist and leverage your expertise to make a lasting impact in the rapidly evolving world of AI and healthcare.
Mandatory: AWS MLOps (Primary) Data Science Machine Learning, Python. Extensive experience and understanding of the Dataiku DSS MLOPs capability including automated deploying projects and published jobs into Production.. Experience in using core analytics methods, Predictive Modeling, Machine Learning, Simulation, and Optimization.. Expertise in a variety of machine learning and statistical techniques (clustering, decision tree learning, artificial neural networks, etc.. Understanding of the underlying data systems such as AWS Cloud architectures, PySpark, or SQL is a must.
With a commitment to innovation, the company delivers commissioning, validation, and IT services, empowering clients to achieve operational excellence through cutting-edge technologies like AI and machine learning.. Build and deploy AI/ML models using cloud platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch), ensuring alignment with business objectives.. Proficiency in programming languages such as Python, Java, or Scala, and AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).. Preferred certifications: AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer, or equivalent.. Global Practice Architect, FSI, Google Cloud
6 years of experience in a statistical programming language (e.g., Python).. Experience in Artificial Intelligence applications (e.g., deep learning, natural language processing, computer vision, or pattern recognition), applied machine learning techniques, or using OSS frameworks (e.g., TensorFlow, PyTorch).. Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (e.g., using Terraform).. As a Field Solutions Architect, you will play a pivotal role in supporting the Google Cloud sales organization.. Your primary responsibility will be to construct rapid prototype Generative AI applications tailored to Google Cloud customers.
Bachelors or masters degree in computer science, Data Science, Machine Learning, or a related field. Proficiency in programming languages such as Python or R, with expertise in ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong knowledge of Azure cloud services, including Azure Machine Learning, Data Factory, and Cognitive Services. Familiarity with natural language processing (NLP), computer vision, or predictive analytics. Knowledge of big data technologies (e.g., Spark, Hadoop) and data pipeline development.
Octave-X's mission is to revolutionize technology by developing intelligent systems that amplify human potential. We are seeking a Machine Learning Engineer to join our team in Chicago. Experience with machine learning frameworks like TensorFlow, PyTorch, or similar. Experience with deep learning, reinforcement learning, or natural language processing. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
As the nations 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.
Proficient with one or more programming languages (Python, R, Java, C. Experience working with TensorFlow, SciKit Learn, NumPy, SciPy. Experience working with NLP and BERT. Experience implementing deep learning. Experience implementing agile approach to artificial intelligence algorithm development
Build with AWS and Azure cloud computing services providing the necessary infrastructure, resources, and interfaces to enable data loading and LLM workflows.. Use Python/Java and large-scale data workflow orchestration platforms e.g. Airflow to construct software artifacts for ETL, interfacing with diverse data formats and storage technologies, and incorporate them into robust data workflows and dynamic systems. Proficiency in machine learning and and deep learning algorithms such as Deep learning, NLP, Neural networks, multi-class classifications, decision trees, support vector machines,. Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc.. Master's degree or above in Machine learning/data science, computer science, applied mathematics or otherwise research-based field
As the nations 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 applications Solve 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.
Seeking a Machine Learning Engineer to maintain, enhance, and productionize an existing predictive model that estimates the average duration of construction jobs.. You’ll work with historical workflow data, improve model accuracy, and explore new ML opportunities once the current model is stable.. Python – strong proficiency for data manipulation & model implementation.. Applied Machine Learning – hands-on experience with regression, classification, or similar predictive modeling techniques.. Work with historical workflow data to refine accuracy and reliability.
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.)
As a Machine Learning Engineer at Loop, you’ll help turn advanced data capabilities into products that make it easier for merchants to run and grow their businesses.. For ML model development and deployment, we use the AWS ML ecosystem, Airflow, Kubernetes, and Fast API, among other tools.. Our backend data infrastructure is supported by Fivetran, dbt, Snowflake, Hex, Secoda, GoodData.. Proficient in Python and familiar with ML libraries such as Scikit-Learn, PyTorch, or TensorFlow.. Knowledge of container technologies like Docker and orchestration tools like Kubernetes.
Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions.. Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc.. Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras.. Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms.. Exposure in developing API using Flask/Django.
3+ years of building machine learning models for business application experience including predictive modelling, natural language processing, and deep learning.. 2+ years of experience with cloud services related to machine learning (e.g., Amazon SageMaker) and coding with Python or R, using modern machine learning libraries and tools such as scikit-learn, TensorFlow, PyTorch. AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, VPC) and professional certifications (e.g., Solutions Architect Professional).. 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow.. Data Scientist, RWE Clinical Trials - Remote
The Machine Learning Engineer will have a blend of software engineering, cloud engineering, and data science expertise.. REQ: 2+ years of experience in building, training, fine-tuning and shipping machine learning, Generative AI, deep learning models into production using cloud services (e.g., Azure ML Ops, AWS Bedrock) and libraries such as TensorFlow or PyTorch. REQ: Confidence with managing code lifecycle with Azure DevOps or Github. REQ: Extensive architecture and data modeling skills required to ship products using industry-standard data and cloud technologies (e.g., AWS Glue, Apache Airflow, Databricks, Azure Data Factory); certifications are plus. REQ: Theoretical fluency and working proficiency in the application of a broad array of statistical methods such as description and inferential statistics, multivariate regression, clustering, neural networks, predictive modeling, forecasting, machine learning, data mining, and optimization algorithms.
We are looking for an enthusiastic Senior GenAI and LLM Architect to add to Credera's Data capability group. Experience with a variety of ML and AI techniques (e.g. multivariate/logistic regression models, cluster analysis, predictive modeling, neural networks, deep learning, pricing models, decision trees, ensemble methods, etc. Proficiency in programming languages such as Python, TensorFlow, PyTorch, or Hugging Face Transformers for model development and experimentation.. Strong understanding of NLP fundamentals, including tokenization, word embeddings, language modeling, sequence labeling, and text generation.. Experience with designing and presenting compelling insights using visualization tools (RShiny, R, Python, Tableau, Power BI, D3.