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Nooks is the AI Sales Assistant Platform (ASAP) that automates the busywork so reps can focus on the human part of selling and generate more sales pipeline. Our approach involves LLM embeddings, few-shot learning, data labeling, and continuous monitoring of model performance in prod. Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. Full stack ML Eng chops: proficiency in general purposes programming languages such as Python/Javascript, and with libraries like TensorFlow, PyTorch, Keras, scikit-learn etc. Expertise in areas like NLP, Deep Learning, Anomaly Detection, Transformers and Large Language Models.
Equilibrium Energy is revolutionizing the clean energy transition by developing innovative grid-scale energy storage solutions.. Formulate and apply novel machine learning solutions to the energy domain : Tackle complex deep learning & machine learning problems by researching published academic literature, surveying industry techniques & intuition, and executing hands-on experimental testing & modeling.. Passion for clean energy and fighting climate change. 4+ years experience in data science, research science, machine learning, or similar role, applying and adapting deep learning, graph neural networks, or reinforcement learning techniques to time series regression & forecasting problems. 3+ years experience with python and the supporting computational science tool suite (e.g. numpy, scipy, pandas, scikit-learn, tensorflow, etc.)
We’re seeking a Senior Machine Learning Engineer to join our Data Services and Moderation team within Unity Ads!. You’ll collaborate with teams of data scientists, software developers, and product managers to design, develop, and deploy various deep learning and LLM/RAG solutions, and ensure their integration into our Unity Ads infrastructure. Proficient and strong knowledge in Python, Terraform, cloud platforms (GCP/AWS), Docker, K8, Kafka, Github Actions, serverless, and SQL. Familiar with Numpy, Tensorflow, Pytorch, vector DB, neural networks, computer vision, LLM, RAG and general ML concepts. Proficiency in data manipulation and analysis using tools like SQL, BigQuery, Pandas, and/or Spark, along with experience in data visualization and dashboarding.
Have built backend production services on cloud environments like (but not limited to) AWS, using languages Python, Terraform, and other similar technologies. Have built and worked on data pipelines using large scale data technologies (like Spark, SQL, Snowflake).. 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.. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Sign in to set job alerts for “Machine Learning Engineer” roles.
Responsible for the development, enhancement, and production of various predictive and Machine Learning driven models to generate behavioral shopper insights, target audiences, and optimized customer journeys.. Knowledge of machine learning, information retrieval, data mining, statistics, NLP or related field.. Experience managing end-to-end machine learning pipeline from data exploration, feature engineering, model building, performance evaluation, and online testing with big data set.. MUST HAVE minimum 3 years of hands-on experience of SQL in Hive/Hadoop/Google Cloud Platform environments.. Practical experience in mining, analyzing and interpreting data through various statistical techniques and predictive models (e.g. Regression, Time Series, Natural Language Processing, Pattern Recognition, Classification, Segmentation, Deep Learning).
Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows.. 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role. Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow). More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.. Solutions Architect - Digital Native Business Solutions Architect, Conversational AI & Prompt Engineering Senior AI Solutions Engineer (pre-sales) Sunnyvale, CA $180,000.00-$205,000.00 1 week ago
As a Senior Solutions Architect on the Digital Native Strategic team, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role.. Expertise in one of the following:Data Engineering technologies (Ex: Spark, Hadoop, Kafka)Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow).. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
Optimizing RAG pipelines, agent architectures, and LLM-powered systems. Strong Python skills with frameworks like TensorFlow, PyTorch, or JAX. Experience with big data tools (Apache Spark, Kafka, Hadoop) and MLOps platforms. Familiarity with cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes). Technologies You Might Work With: Python, TensorFlow, PyTorch, JAX, Kubernetes, Docker, MLflow, Kubeflow, FastAPI, SQL, NoSQL, Airflow, Spark, Kafka, Hadoop, AWS (SageMaker, Lambda, S3), GCP (Vertex AI, BigQuery), Azure (ML Studio, Synapse).
We are seeking mid-level Artificial Intelligence engineers who will help develop AI technologies that adapt and scale to solve sophisticated problems across a variety of problem domains.. A general understanding of machine learning algorithms including deep learning, neural network design, deep reinforcement learning, large language models (LLMs), and computer vision.. Common machine learning frameworks such as PyTorch, TensorFlow, or Jax. LLM frameworks such as HuggingFace, including retrieval-augmented (LangChain, Llama-Index) optimizing / agentic LLM stacks (DSPy, Smolagents, etc), and parameter-efficient fine-tuning (LoRA, Q-LoRA).. LLM inference servers (TGI, vLLM, etc).
We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society.. We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments.. BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.. or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.. Deep understanding of state-of-the-art machine learning techniques and models.
At Upscale AI, we are building the industrys first holistic marketing solution that makes it easy for DTC and e-commerce brands to run performance campaigns on Streaming TV - in a way that leverages their best brand, product & social content.. We are seeking a highly skilled Machine Learning Engineer with extensive experience in TensorFlow, PyTorch, Google Colab, reinforcement learning, generative AI, and image and video processing to join our dynamic team.. Strong proficiency in Python and deep learning frameworks such as TensorFlow and PyTorch.. Experience with natural language processing (NLP).. Machine Learning Engineer for Game Technology
AIML - Machine Learning Engineer. The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing!. As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence.. Experience working with Deep learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning and model evaluation. Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, PyTorch, or JAX.
Deep understanding of AI/ML concepts with expert knowledge in Large Language Models, Deep Learning, Neural Networks, NLP. MSc or PhD in a quantitative field, e.g., Computer Science, NLP, AI, Machine Learning. 5+ years of experience in Deep Learning, Neural Networks, Generative AI, Knowledge graph, NLP and relevant frameworks. Experience with common analytics and data science frameworks: PyTorch, NumPy, sci-kit-learn, pandas, Keras, TensorFlow, etc. Job Segment: Research Engineer, Training, Computer Science, Compliance, Engineering, Research, Education, Technology, Legal
Master's or PhD in Electrical or Computer Engineering, Statistics, Mathematics, or Data Science domains.. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.. Experience with cloud platforms such as AWS, Azure, or Google Cloud.. Familiarity with big data technologies like Hadoop, Spark, or Kafka.
As a member of our team, you’ll 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.
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.
As the Director of Machine Learning on the Data, Growth & Platforms team focused on Digital Media, you will lead a high-impact, multidisciplinary team of ML/AI engineers and data scientists dedicated to transforming Adobes go-to-market (GTM) and revenue strategies through machine learning.. Innovation & Business Impact: Apply innovative ML research, including recommender systems, reinforcement learning, predictive modeling, and causal inferenceto GTM domains.. MS or PhD in Computer Science, Machine Learning, or a related technical field.. Deep experience in training and deploying deep learning models using frameworks like TensorFlow and PyTorch.. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
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)
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.
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)