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🔥 ML Engineer (Focus on NLP Technologies)
Posted about 12 hours ago

📍 Brazil, Argentina, Colombia

🔍 Software Development

🏢 Company: NineTwoThree AI Studio

  • Knowledge of Machine Learning fundamentals.
  • Background in integrating ML models into data-driven systems.
  • Experience with Python and SQL, along with expertise in NLP and LLMs.
  • Ability to quickly adapt to new technologies and problem domains.
  • Familiarity with ML deployment and monitoring.
  • Proven experience in machine learning and natural language processing.
  • An understanding of general LLM architecture and limitations, as well as features of modern LLMs.
  • Experience with cloud computing services, preferably AWS.
  • Proficiency in Python and familiarity with ML frameworks like TensorFlow or PyTorch.
  • Excellent problem-solving skills and ability to work independently.
  • Strong communication skills and ability to collaborate in a team environment.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
  • Develop and maintain advanced machine learning models, particularly focusing on natural language processing and understanding.
  • Implement and optimize ML solutions for various client applications.
  • Work closely with the development team to integrate AI models into existing systems.
  • Experiment with new models and techniques to improve performance and capabilities.
  • Participate in code reviews, maintain high coding standards, and contribute to our internal knowledge base.
  • Stay abreast of the latest developments in AI and machine learning.

AWSPythonSQLCloud ComputingMachine LearningPyTorchTensorflow

Posted about 12 hours ago
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🔥 Senior Machine Learning Engineer - Behaviors
Posted about 12 hours ago

📍 United States

💸 146000.0 - 225000.0 USD per year

🔍 Software Development

🏢 Company: Motional👥 1001-5000💰 Seed about 1 year ago🫂 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, and  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 12 hours ago
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🔥 AI Solutions Lead (Remote)
Posted about 14 hours ago

📍 United States

💸 110000.0 - 190000.0 USD per year

🔍 Cybersecurity

🏢 Company: crowdstrikecareers

  • 10+ years of combined experience in Business Data Integrations, AI/ML development, AI-driven automation and enterprise technology leadership.
  • Strong ability to understand functional business requirements, size AI efforts, and develop/lead AI automation solutions.
  • Expertise in AI vs. automation decision-making, selecting the right approach based on business needs.
  • Hands-on experience building and deploying LLMs, AI agents, and machine learning models in real-world applications.
  • Proficiency in Python, R, or Java, with experience in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Deep understanding of enterprise business data (CRM, ERP, Finance, HR systems) and how AI can enhance decision-making.
  • Experience integrating AI solutions with enterprise data platforms such as Snowflake, AWS/GCP/Azure Data Lakes, Salesforce, ERP, HR, and Finance applications.
  • Proven ability to work with product managers and business analysts to prioritize AI projects and develop execution plans.
  • Strong understanding of MLOps best practices, including model versioning, monitoring, and retraining.
  • Experience leading and mentoring AI developers, fostering innovation and technical excellence.
  • Excellent communication and leadership skills, with the ability to present AI strategies and insights to executive stakeholders.
  • Understand and translate functional requirements from business units into AI-driven solutions, ensuring alignment with enterprise goals.
  • Evaluate and size AI efforts, differentiating between automation vs. AI-driven approaches to optimize implementation strategies.
  • Collaborate with product managers and business analysts to prioritize AI initiatives, develop roadmaps, and execute strategies.
  • Lead AI development teams, guiding engineers and data scientists in designing and deploying LLMs, AI agents, and intelligent automation solutions.
  • Architect and implement machine learning models and AI-driven automation frameworks, integrating them into enterprise applications.
  • Work with CRM, ERP, and other enterprise data platforms (Salesforce, SAP, Workday, NetSuite) to leverage structured and unstructured data for AI use cases.
  • Ensure AI solutions align with enterprise security, compliance, governance, and ethical AI standards.
  • Evaluate buy vs. build decisions for AI tools and frameworks, aligning with business needs and technical feasibility.
  • Foster cross-functional collaboration between data engineers, developers, and business teams to ensure seamless AI integration.

AWSLeadershipPythonArtificial IntelligenceBusiness IntelligenceCloud ComputingData AnalysisGCPMachine LearningPyTorchSalesforceSAPSnowflakeAlgorithmsAzureData engineeringData scienceData StructuresRDBMSTensorflowCommunication SkillsRESTful APIsData visualizationData modeling

Posted about 14 hours ago
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🔥 AI Safety Researcher
Posted about 17 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Trace Machina👥 11-50💰 $4,700,000 Seed 7 months agoIT InfrastructureRoboticsSoftware

  • 3+ years of experience in AI/ML research, with a focus on safety, robustness, and interpretability
  • Strong background in machine learning theory, with practical experience implementing models and algorithms
  • Expertise in AI safety frameworks, fault tolerance, and risk mitigation strategies for AI systems
  • Experience with reinforcement learning, adversarial training, and robustness testing of AI models
  • Proficiency in programming languages such as Python, C++, or Go, with hands-on experience in AI development libraries (e.g., TensorFlow, PyTorch)
  • Strong understanding of AI ethics, fairness, and the impact of machine learning algorithms in real-world applications
  • Ability to identify potential safety risks in AI-driven systems and design solutions to address them
  • Familiarity with distributed systems, cloud infrastructure, and build/test automation frameworks
  • Conduct research into AI safety, focusing on robustness, fairness, and interpretability of machine learning models used in build systems
  • Develop algorithms and frameworks that ensure the safe deployment of AI-powered automation in software build, testing, and CI/CD workflows
  • Work closely with engineering teams to integrate AI safety mechanisms and ensure robust error handling and fault tolerance
  • Investigate and mitigate risks associated with AI-driven decision-making in distributed build systems, especially in mission-critical operations
  • Contribute to the development of safety-critical AI models for optimizing performance, caching accuracy, and task coordination across various customer environments
  • Conduct studies on the ethical implications of AI in software development, ensuring that algorithms used in NativeLink align with responsible AI principles
  • Perform in-depth testing, model validation, and risk assessment to ensure AI systems meet reliability and safety standards
  • Collaborate with product managers and engineers to translate research findings into practical tools and features for our customers

PythonMachine LearningPyTorchC++GoTensorflowCI/CD

Posted about 17 hours ago
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🔥 Data Scientist - AI/ML
Posted about 21 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Trace Machina👥 11-50💰 $4,700,000 Seed 7 months agoIT InfrastructureRoboticsSoftware

  • 3+ years of experience as a Data Scientist, with a strong focus on AI and machine learning
  • Expertise in machine learning algorithms, data analysis, and statistical modeling techniques
  • Proficiency in Python, R, or other data science programming languages, with experience using libraries such as TensorFlow, PyTorch, Scikit-learn, and Pandas
  • Strong knowledge of deep learning, reinforcement learning, or other advanced AI techniques
  • Experience with large-scale data processing, including working with big data technologies (e.g., Spark, Hadoop)
  • Familiarity with cloud infrastructure (AWS, GCP, Azure) and deploying machine learning models in production
  • Strong understanding of data wrangling, feature engineering, and building predictive models
  • Experience with version control (Git) and working in collaborative environments
  • Excellent problem-solving skills and ability to generate actionable insights from data
  • Ability to communicate complex AI/ML concepts effectively to both technical and non-technical teams
  • Design, implement, and deploy machine learning models to optimize software build systems, including caching, task distribution, and execution workflows
  • Work with large datasets to identify patterns, anomalies, and insights that inform decisions for improving build processes and remote execution
  • Develop predictive models to optimize build times, cache hit rates, and system resource utilization
  • Conduct experiments to improve the efficiency of build systems through data-driven decisions, leveraging AI/ML techniques such as reinforcement learning and optimization
  • Collaborate with cross-functional teams (engineering, product, and operations) to translate business problems into AI/ML-driven solutions
  • Analyze customer usage data to identify opportunities for feature improvements and innovations within the NativeLink platform
  • Develop custom algorithms for performance monitoring, anomaly detection, and optimization of CI/CD pipelines
  • Build, test, and validate machine learning models using a variety of techniques, ensuring they are scalable, robust, and interpretable
  • Build and maintain data pipelines to support model training, testing, and deployment in production environments
  • Communicate findings and insights to both technical and non-technical stakeholders in a clear and actionable way

AWSPythonCloud ComputingData AnalysisGCPGitHadoopMachine LearningPyTorchAzureData sciencePandasSparkTensorflowCI/CDData visualization

Posted about 21 hours ago
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🔥 Senior Software Engineer (Python)
Posted about 21 hours ago

📍 United States

🧭 Full-Time

🔍 Healthcare Technology

🏢 Company: Humata Health, Inc

  • 5+ years of professional Python development experience in production environments
  • 3+ years of experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
  • Strong experience with MLOps practices and tooling (model versioning, feature stores, experiment tracking)
  • Experience deploying and monitoring ML models in production environments
  • Proficiency with containerization (Docker) and orchestration (Kubernetes)
  • Experience with cloud platforms (AWS, GCP, or Azure) and their ML services
  • Strong understanding of data processing techniques and libraries (Pandas, NumPy)
  • Proficiency with version control systems (Git) and CI/CD pipelines
  • Develop scalable, high-performance Python applications that can handle significant data volumes and interface over gRPC
  • Design, build and maintain highly observable Python microservices that work seamlessly with our Golang service backend
  • Create reproducible, scalable, and monitored ML workflows from experimentation to production
  • Implement robust data processing pipelines for healthcare data
  • Build and maintain RESTful APIs and backend services that integrate with our ML systems
  • Collaborate with data scientists to operationalize models and improve model performance
  • Establish MLOps best practices, including CI/CD for ML, model versioning, and monitoring
  • Troubleshoot, debug, and optimize existing ML systems for performance and reliability
  • Work with cross-functional teams to define requirements and implement new features
  • Mentor junior engineers and contribute to engineering excellence

AWSBackend DevelopmentDockerPostgreSQLPythonSoftware DevelopmentSQLGCPGitKubernetesMachine LearningNumpyPyTorchAlgorithmsData engineeringData StructuresgRPCREST APIPandasTensorflowCI/CDRESTful APIsMicroservicesSoftware EngineeringData analyticsDebugging

Posted about 21 hours ago
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🔥 Manager, Engineering -MarTech (Remote)
Posted about 21 hours ago

📍 United States

💸 115000.0 - 230000.0 USD per year

🔍 Insurance

🏢 Company: external

  • Fluency and specialization with Java, Python and SQL
  • Experience with AI and ML technologies including MLflow, PyTorch and VectorDBs, Scikit-learn and Langchain
  • Experience with data processing, ETL, DataRobot and Snowflake
  • Experience building products of micro-services-oriented architecture and extensible REST APIs
  • Experience building the architecture and design of new and current systems (architecture, design patterns, reliability, security, and scaling)
  • Fluency in DevOps Concepts, Cloud Architecture and Azure DevOps Operational Framework
  • Experience with application monitoring tools and performance assessments
  • In-depth knowledge of CS data structures and algorithms
  • Experience with solving analytical problems with quantitative approaches
  • Ability to excel in a fast-paced, startup-like environment
  • Exemplary ability to design, perform experiments, and influence engineering direction and product roadmap
  • Experience partnering with engineering teams and transferring research to production
  • Work with your Director to address project dependencies, negotiate and estimate incremental delivery dates for milestones with the stakeholder community, and deliver projects on time
  • Identify and raise appropriate project risks, in addition to presenting detailed and implementable solutions or alternatives
  • Understand how requirements and design choices may impact systems across multiple areas
  • Report on your team’s progress for project and other key metrics, in addition to presenting detailed and implementable ideas for areas to further improve or influence product or project delivery
  • Initiate and support performance evaluation of team members
  • Cultivate a culture that motivates all levels of performers to higher levels of achievement
  • Build and maintain relationships with your team members to support an environment of trust
  • Influence those you motivate and coach to be receptive to feedback by cultivating a culture that acknowledges and expects individuals to grow and be accountable as a result of the experience gained (growth mindset)
  • Identify where technical or analytical skill gaps put future team deliverables at risk and craft a plan to remediate, consistently challenge team members to share knowledge and learn new technologies
  • Proficiently execute difficult conversations on development and performance
  • Craft and deliver strategic and well-structured persuasive arguments to drive projects that drive process improvement, enhance cost leadership, and/or customer experience
  • Manage up to leadership as well as give feedback when appropriate
  • Administer coaching plan(s) and Performance Improvement Plan(s)
  • Craft fully compliant quality documentation
  • Compliant negotiation and execution of warning administration and/or involuntary termination
  • Develop the team budget and be accountable for reporting on results achieved at regular intervals
  • Significantly contribute to the team planning process to include surfacing associate level proposals

DockerLeadershipPythonSQLCloud ComputingETLJavaKubernetesMLFlowPyTorchSnowflakeAlgorithmsData StructuresREST APIDevOpsMicroservices

Posted about 21 hours ago
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🔥 Sr. Applied Machine Learning Researcher - Generative Models (US Remote)
Posted 1 day ago

📍 United States

🧭 Full-Time

💸 170734.0 - 213418.0 USD per year

🔍 Software Development

🏢 Company: Splice👥 101-250💰 $55,000,000 Series D about 4 years agoMedia and EntertainmentMusicMachine LearningSoftware

  • Ph.D. or Master's degree in Electrical Engineering, Computer Science or related Engineering discipline.
  • Background or proven experience in Digital Signal Processing.
  • Proven experience (2+ years) in an Applied Research role focused on Latent Diffusion based generative models for audio and/or symbolic music generation using Transformer-based architectures.. Alternatively, solid experience with diffusion-based models in the image domain, would be considered.
  • Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
  • Familiarity with software development best practices and version control systems (e.g., Git).
  • Strong communication and collaboration skills, with the ability to work cross-functionally with stakeholders in Engineering, Product and Design.
  • Conduct literature research and experimentation in the field of ML-based generative audio using Latent Diffusion and symbolic music generation using Transformer-based architectures.
  • Collaborate with our ML Engineers to design performant model architectures for efficient ML-based audio synthesis and symbolic music generation, as well as adapting and fine-tuning existing models.
  • Develop proof-of-concept prototypes to showcase and validate capabilities and use cases using generative audio/symbolic models.
  • Engage with academic and open source communities to stay up to date with the latest developments in the space, collaborate in joint projects, and identify top talent for our AI & Audio Science team’s future hiring needs.
  • Stay up-to-date with the latest academic and industrial research in generative models for music, incorporating relevant findings into our applied research and product development processes.
  • Document research findings, methodologies, and best practices. Collaborate with team members to disseminate knowledge and insights.

PythonSoftware DevelopmentSQLData AnalysisGitImage ProcessingMachine LearningNumpyPyTorchAlgorithmsData StructuresTensorflowCommunication SkillsCollaborationCI/CDRESTful APIsDocumentationPrototypingSoftware Engineering

Posted 1 day ago
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🔥 Staff Software Engineer, ML Understanding
Posted 1 day ago

📍 Ireland, the Netherlands, the United Kingdom

🔍 Software Development

🏢 Company: Reddit👥 1001-5000💰 $410,000,000 Series F over 3 years ago🫂 Last layoff almost 2 years agoNewsContentSocial NetworkSocial Media

  • 7+ years of relevant experience as a software engineer involved in projects related with natural language processing and AI models integration in products.
  • Strong background in Python programming and some experience with deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Expertise in distributed training frameworks (e.g., Ray Training, PyTorch Distributed), and efficient utilization of hardware resources.
  • Proficiency in data preprocessing, tokenization, embeddings, and language modeling techniques.
  • Passion for developing scalable, well-designed, and responsible AI solutions that positively impact society.
  • Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams.
  • Entrepreneurial spirit, self-motivation, and a bias towards action in fast-paced environments.
  • Lead the design, development, and maintenance of the backend and data infrastructure for efficient, accurate, and optimized deployment of AI / ML based systems.
  • Architect and implement scalable AI / ML based solutions that can handle both the long term growth in the size of our data, and the scalability of the support in accessing it across a growing number of needs within the company
  • Collaborate with other teams and functions to work towards consolidating all insights about Reddit’s data to be powered by the same platform.
  • Oversee data storage, retrieval, indexing, and query optimization strategies to ensure fast and reliable access to our data. This may include migrating the data to the right datastore given the company’s growing needs
  • Collaborate with cross-functional teams to gather requirements, define system architectures and support system development.
  • Provide technical guidance and mentorship to engineers on the team, fostering a culture of learning and innovation.
  • Proactively identify technical challenges and propose innovative solutions that align with the team's goals.

AWSBackend DevelopmentPythonArtificial IntelligenceMachine LearningNLTKNumpyPyTorchSoftware ArchitectureAlgorithmsAPI testingData engineeringData scienceData StructuresREST APITensorflowRESTful APIsSoftware EngineeringData management

Posted 1 day ago
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🔥 Senior Machine Learning Engineer, Top Of Funnel
Posted 1 day ago

📍 UK, Ireland, Netherlands

🧭 Full-Time

🔍 Software Development

🏢 Company: Reddit👥 1001-5000💰 $410,000,000 Series F over 3 years ago🫂 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)
  • 4+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models
  • 4+ years of experience of orchestrating complicated data generation pipelines on large-scale dataset
  • Successful track record of productionizing and applying machine learning techniques in addressing real-world problems end to end.
  • Comfort analyzing high-volume natural language and multimodal data from varying sources, proficient with SQL
  • Experience working with data-intensive systems and writing production-quality software (preferred Python or golang)
  • Collaborate on projects with other Top of Funnel engineers where you’ll apply Machine Learning to solve discovery, relevance and recommendation problems.
  • Build and deploy sophisticated machine learning models to improve experiences for millions of users.
  • Participate in the full software development cycle: design, develop, QA, deploy, experiment, analyze and iterate.
  • Collaborate across disciplines and with other ML teams at Reddit to find technical solutions to complex challenges.
  • Be a mentor and cross-functional advocate for the team

PythonSQLData AnalysisMachine LearningPyTorchAlgorithmsData engineeringData StructuresTensorflowRESTful APIsData visualizationData modeling

Posted 1 day ago
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