Apply

Machine Learning Engineer

Posted 1 day agoViewed

View full description

πŸ“ Location: United States

πŸ’Έ Salary: 215000.0 - 250000.0 USD per year

πŸ” Industry: AI

🏒 Company: ElicitπŸ‘₯ 11-50πŸ’° $9,000,000 Seed over 1 year agoDatabaseArtificial Intelligence (AI)Data Center AutomationInformation Technology

πŸͺ„ Skills: PythonSoftware DevelopmentData AnalysisMachine LearningAlgorithmsSoftware Engineering

Requirements:
  • Strong software engineering background.
  • Familiar with language models (training, fine-tuning, evaluation), or have a comparable machine learning or natural language processing background (e.g. experience with information extraction, semantic search)
Responsibilities:
  • Compose together tens to thousands of calls to language models to accomplish tasks that we can't accomplish with a single call.
  • Curate datasets for finetuning models, e.g. for training models to extract policy conclusions from papers
  • Set up evaluation metrics that tell us what changes to our models or training setup are improvements
  • Scale up semantic search from a few thousand documents to 100k+ documents
Apply

Related Jobs

Apply

πŸ“ United States

πŸ’Έ 146000.0 - 225000.0 USD per year

πŸ” Software Development

🏒 Company: MotionalπŸ‘₯ 1001-5000πŸ’° Seed about 1 year agoπŸ«‚ Last layoff 11 months agoAutomotiveFleet ManagementInformation TechnologyAutonomous VehiclesSoftware

  • In-depth understanding of common Machine Learning and Deep Learning algorithms
  • Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
  • Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
  • Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, andΒ  testing methods
  • Experience with PyTorch or other python-based deep learning frameworks
  • Experience working with large data sets and deriving insights from data
  • Experience mentoring and collaborating with others
  • Designing and executing high value experiments based on collaborative input from other machine learning engineers
  • Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
  • Timely release of major model updates, including analysis of both off-line and on-road evaluation data
  • Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
  • Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

PythonData AnalysisImage ProcessingMachine LearningNumpyPyTorchC++AlgorithmsData StructuresSoftware Engineering

Posted about 2 hours ago
Apply
Apply

πŸ“ United States

πŸ’Έ 140000.0 - 155000.0 USD per year

πŸ” News

🏒 Company: The New York Times

  • 4+ years of software-engineering experience
  • 2+ years of developing applications with machine-learning models
  • Experience in a newsroom or collaborating with journalists or other creative professionals on software development
  • Technical proficiency and recent experience working with large-language and transformer models
  • Deep knowledge of machine-learning frameworks
  • Experience evaluating the strengths and weaknesses of different A.I. models
  • Full-stack engineering skills for developing front-end web applications and agents with server-side components
  • Build prototypes that use machine-learning techniques for the betterment of The Times news report
  • Develop new algorithms, fine-tuning large-language models, and create other infrastructure for the team’s work
  • Collaborate with the A.I. team and other desks in the newsroom to assess the value of each prototype and help determine those worth pursuing further
  • Stay up-to-date on the latest A.I. research and model development, to help inform the team’s work and spread technical proficiency throughout the organization
  • Develop relationships with other technologists in the newsroom and on product teams, to learn from their existing work with A.I.
  • Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

PythonSoftware DevelopmentFrontend DevelopmentFull Stack DevelopmentMachine LearningAlgorithms

Posted 1 day ago
Apply
Apply

πŸ“ Brazil, the U.S., and Canada

🧭 Full-Time

πŸ” Payments

  • Bachelor’s or Master’s degree in CS/Engineering/Data-Science or other technical disciplines.
  • Solid experience in DS/ML engineering.
  • Proficiency in programming languages such as Python, Scala, or Java.
  • Hands-on experience in implementing batch and real-time streaming pipelines, using SQL and NoSQL database solutions
  • Familiarity with monitoring tools for data pipelines, streaming systems, and model performance.
  • Experience in AWS cloud services (Sagemaker, EC2, EMR, ECS/EKS, RDS, etc.).
  • Experience with CI/CD pipelines, infrastructure-as-code tools (e.g., Terraform, CloudFormation), and MLOps platforms like MLflow.
  • Experience with Machine Learning modeling, notably tree-based and boosting models supervised learning for imbalanced target scenarios.
  • Experience with Online Inference, APIs, and services that respond under tight time constraints.
  • Proficiency in English.
  • Design the data-architecture flow for the efficient implementation of real-time model endpoints and/or batch solutions.
  • Engineer domain-specific features that can enhance model performance and robustness.
  • Build pipelines to deploy machine learning models in production with a focus on scalability and efficiency, and participate in and enforce the release management process for models and rules.
  • Implement systems to monitor model performance, endpoints/feature health, and other business metrics; Create model-retraining pipelines to boost performance, based on monitoring metrics; Model recalibration.
  • Design and implement scalable architectures to support real-time/batch solutions; Optimize algorithms and workflows for latency, throughput, and resource efficiency; Ensure systems adhere to company standards for reliability and security.
  • Conduct research and prototypes to explore novel approaches in ML engineering for addressing emerging risk/fraud patterns.
  • Partner with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions.

AWSBackend DevelopmentDockerPythonSQLAmazon RDSAWS EKSFrontend DevelopmentJavaKafkaKubernetesMachine LearningMLFlowAirflowAlgorithmsData engineeringData scienceREST APINosqlPandasSparkCI/CDTerraformScalaData modelingEnglish communication

Posted 2 days ago
Apply
Apply

πŸ“ US

🧭 Full-Time

πŸ” Software Development

🏒 Company: YobiπŸ‘₯ 11-50πŸ’° $2,370,000 Seed about 2 years agoCRMElectronicsBig DataB2BSoftware

  • Can think creatively about data
  • Knows when to use a Data Clean Room
  • Understanding enough about machine learning to be dangerous
  • Worked on and can speak to some kinds of impactful consumer-facing ML problem, e.g. recommender systems, personalization, etc.
  • Building systems to ingest partner data in a privacy-safe way
  • Getting the most out of the data to power the rest of our models and products
  • Collaborating with the Product org
  • Working with customers directly

PythonSQLApache AirflowData AnalysisMachine LearningProduct ManagementAlgorithmsData engineeringSparkCI/CDData modeling

Posted 5 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ” AdTech

🏒 Company: YobiπŸ‘₯ 11-50πŸ’° $2,370,000 Seed about 2 years agoCRMElectronicsBig DataB2BSoftware

  • AdTech experience and product intuition for the space
  • Understanding enough about machine learning
  • Skill and attitude wise, can quickly contribute to things such as orchestration/Airflow, Bazel (build systems, really), CI/CD, Spark (we have both Python and Scala), and other SQL-y data computation backends as needed.
  • Focus on the models, metrics, pipelines, systems, and services that power and deliver excellence via Yobi Applications products
  • Involve a large degree of 0-to-1 development
  • Rely on collaboration with Product, core signals MLEs, and leaning on your own expertise and insight in building holistic ML-powered products.

PythonSQLApache AirflowMachine LearningProduct ManagementAlgorithmsData engineeringData scienceSparkCI/CDRESTful APIsScala

Posted 5 days ago
Apply
Apply

πŸ“ United States, Canada

🧭 Full-Time

πŸ’Έ 127000.0 - 158700.0 USD per year

πŸ” Remote Sensing

🏒 Company: PlanetπŸ‘₯ 501-1000πŸ’° $200,000,000 Post-IPO Equity over 3 years agoπŸ«‚ Last layoff 9 months agoGeospatialRemote SensingBig DataAerospaceAnalyticsSoftware

  • Bachelor's or Master's degree in Computer Science or a related field
  • 4+ years of professional experience in software engineering of which 2+ years of this is experience in developing and designing Computer Vision and/or Machine Learning technologies and systems
  • Proficiency with Python and machine learning frameworks like TensorFlow or PyTorch
  • Proficiency with software engineering best practices such as version control, testing and continuous integration/continuous deployment (CI/CD)
  • Experience with containerization and container orchestration tools like Docker, Kubernetes, Flyte or Temporal
  • Experience implementing model versioning, monitoring and observability systems
  • Establish and maintain machine learning operations workflows for regular data generation
  • Run experiments to evaluate machine learning algorithms
  • ML operations to maintain production algorithms (monitoring, training, benchmarking, deploying, etc)
  • Develop and implement automated testing to ensure the reliability of deployed models
  • Contribute to full-stack development, from backend and APIs to DevOps tasks and occasional front-end work

DockerPythonData AnalysisImage ProcessingKubernetesMachine LearningPyTorchAlgorithmsTensorflowCI/CDRESTful APIsDevOpsSoftware Engineering

Posted 6 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ’Έ 185800.0 - 260100.0 USD per year

🏒 Company: RedditπŸ‘₯ 1001-5000πŸ’° $410,000,000 Series F over 3 years agoπŸ«‚ Last layoff almost 2 years agoNewsContentSocial NetworkSocial Media

  • 2+ years of experience with industry-level deep learning models.
  • 2+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch).
  • 3+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models.
  • 3+ years of experience of orchestrating complicated data generation pipelines on large-scale datasets.
  • Experience working with cross functional stakeholders across research, product & infrastructure to productize ML research
  • Knowledge of large scale search & recommender systems, or modern ads ranking/retrieval/targeting systems is preferred
  • Experience with deep learning, representation learning or transfer learning is preferred
  • Own end-to-end execution of ML-based targeting products like smart targeting expansion, keyword targeting, auto targeting, user lookalikes etc
  • Own offline & online experimentation of ML models for improving targeting products to drive advertiser outcomes
  • Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two tower models) with a focus on improving advertiser outcomes
  • Drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy
  • Work on large scale data systems, backend services and product integration
  • Collaborate closely with multiple stakeholders cross product, engineering, research and marketing

AWSBackend DevelopmentPythonMachine LearningNumpyPyTorchData engineeringSparkTensorflow

Posted 7 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ’Έ 130000.0 - 200000.0 USD per year

πŸ” Software Development

🏒 Company: Sadaora

  • 5+ years of experience developing, deploying, and maintaining ML models in production environments.
  • Proficiency in Python and common ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Strong foundation in statistics, linear algebra, probability, and optimization.
  • Deep understanding of a range of ML techniques (regression, classification, clustering, NLP, deep learning).
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes).
  • Solid understanding of software engineering principles, version control (Git), and CI/CD workflows.
  • Design, train, and evaluate machine learning models using best-in-class frameworks.
  • Architect scalable ML solutions and pipelines, from feature engineering to deployment.
  • Implement rigorous testing, validation, and monitoring processes to ensure model reliability in production.
  • Work closely with data engineers to shape the data architecture required for robust ML workflows.
  • Build efficient ETL pipelines to clean, preprocess, and transform large-scale datasets.
  • Partner with product managers, engineers, and business stakeholders to define ML use cases.
  • Collaborate with software engineers to integrate ML models into production-grade APIs and applications.
  • Translate complex ML concepts into business-relevant insights and recommendations.
  • Stay current with advancements in machine learning, AI, and related fields.
  • Experiment with new algorithms, architectures, and tools to continuously enhance our capabilities.
  • Contribute to a culture of experimentation, technical excellence, and intellectual curiosity.

AWSDockerPythonETLGCPGitKubernetesMachine LearningMLFlowPyTorchAzureData engineeringTensorflowCI/CD

Posted 9 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ” Software Development

🏒 Company: AnomaloπŸ‘₯ 11-50πŸ’° $10,000,000 Series B 4 months agoData ManagementInformation TechnologySoftware

  • Strong Python expertise (ML engineering, data processing, and API development).
  • Experience deploying GenAI/LLM-based applications (e.g., chatbots, recommendation systems).
  • Familiarity with OpenAI, Anthropic Claude, and similar GenAI platforms.
  • Background in production-scale ML applications, particularly LLMs for enterprise use cases.
  • Develop and deploy GenAI-driven products, including customer-facing applications and internal tools for engineering teams.
  • Work with unstructured data and define product quality standards for a rapidly evolving space.
  • Collaborate with design partners and enterprise customers to understand how ML and LLMs can be applied effectively.
  • Build and refine retrieval-augmented generation (RAG) models and fine-tune LLMs for specific use cases.
  • Own projects from concept to production, ensuring scalability and performance in real-world environments.

AWSPythonMachine LearningAPI testing

Posted 9 days ago
Apply
Apply

πŸ“ United States

🧭 Full-Time

πŸ’Έ 216700.0 - 303400.0 USD per year

πŸ” Software Development

🏒 Company: RedditπŸ‘₯ 1001-5000πŸ’° $410,000,000 Series F over 3 years agoπŸ«‚ Last layoff almost 2 years agoNewsContentSocial NetworkSocial Media

  • 5+ years of experience in machine learning engineering, with a strong focus on recommendation systems, representation learning, and deep learning.
  • Hands-on experience with Graph Neural Networks (GNNs), collaborative filtering, and large-scale embeddings.
  • Proficiency in Python and experience with ML frameworks such as PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, or JAX.
  • Strong understanding of graph theory, network science, and representation learning techniques.
  • Experience building distributed training and inference systems using ML infrastructure components (data parallelism, model pruning, inference optimization, etc.).
  • Ability to work in a fast-paced environment, balancing innovation with high-quality production deployment.
  • Strong communication skills and the ability to collaborate cross-functionally with engineers, researchers, and product teams.
  • Design and implement scalable, high-performance machine learning models using Graph Neural Networks (GNNs), transformers, and knowledge graph approaches.
  • Develop and optimize large-scale embedding generation pipelines for Reddit’s recommendation systems.
  • Collaborate with ML infrastructure teams to enable efficient distributed training (multi-GPU, model/data parallelism) and low-latency serving.
  • Work closely with cross-functional teams (Ads, Feed Ranking, Content Understanding) to integrate embeddings into various personalization and ranking systems.
  • Drive feature engineering efforts, identifying and curating expressive raw data to enhance model effectiveness.
  • Monitor, evaluate, and improve model performance using A/B testing, offline metrics, and real-time feedback loops.
  • Stay up-to-date with the latest research in GNNs, transformers, and representation learning, bringing new ideas into production.
  • Participate in code reviews, mentor junior engineers, and contribute to technical decision-making.

PythonData AnalysisKerasMachine LearningMLFlowPyTorchAlgorithmsData StructuresTensorflowA/B testing

Posted 9 days ago
Apply