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🔥 Director of Data Science
Posted 7 days ago

📍 United States

🧭 Full-Time

🏢 Company: Worth AI👥 11-50💰 $12,000,000 Seed over 1 year agoArtificial Intelligence (AI)Business IntelligenceRisk ManagementFinTech

  • Bachelor’s degree and 8+ years of professional experience, or Master’s degree and 6+ years, or PhD and 4+ years, in a quantitative field such as Computer Science, Statistics, Applied Mathematics, or Engineering.
  • Proven leadership experience managing data science or machine learning teams in fast-paced, agile environments.
  • Deep expertise in statistical modeling and machine learning techniques (e.g., regression, time series, clustering, ensemble methods, simulation, NLP, deep learning, etc.).
  • Hands-on proficiency in Python and SQL; familiarity with R or other languages is a plus.
  • Practical experience with ML libraries and frameworks such as Scikit-learn, TensorFlow, Keras, PyTorch, Statsmodels, NumPy, and SciPy.
  • Strong understanding of data architecture and MLOps practices in cloud environments such as AWS, Azure, or GCP.
  • Excellent data storytelling and executive communication skills; confident in building and delivering compelling visual presentations (e.g., Tableau, PowerBI).
  • Deep understanding of Agile methodologies such as Scrum or Kanban.
  • Lead, mentor, and scale a high-performing team of data scientists while fostering a culture of innovation, collaboration, and continuous learning.
  • Oversee the end-to-end development of machine learning models—design, training, validation, and deployment—within cloud-based production environments.
  • Partner with product, engineering, and business teams to identify opportunities for data science solutions, define success metrics, and deliver measurable impact.
  • Drive the integration of large-scale data systems and pipelines to power intelligent, adaptive models that reflect changing customer, market, and business dynamics.
  • Ensure rigorous model monitoring, governance, and retraining protocols to maintain accuracy, fairness, and compliance.
  • Communicate technical results and strategic insights clearly and persuasively to senior leadership and non-technical stakeholders.
  • Champion the adoption of advanced analytics tools, frameworks, and best practices across the company.

AWSLeadershipPythonSQLAgileCloud ComputingData AnalysisGCPKerasMachine LearningNumpyPyTorchTableauAlgorithmsData scienceData StructuresPandasTensorflowCommunication SkillsData visualizationTeam managementData modeling

Posted 7 days ago
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🔥 Machine Learning Engineer
Posted 8 days ago

📍 Colombia

🧭 Full-Time

🔍 Software Development

  • 5+ years of applied ML engineering experience
  • Develop and Deploy AI Models: Build and deploy machine learning models leveraging NLP techniques and GenAI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base.
  • Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes.
  • Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sagemaker, Lambda, S3, Kendra), MySQL, Airtable, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions.
  • Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zendesk to inform model development and enhance predictive accuracy.
  • Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative GenAI use cases and solutions
  • Develop and Deploy AI/ML Models: Build and deploy machine learning models by leveraging NLP, recommendation systems & GenAI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base.
  • Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes.
  • Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sagemaker, Lambda, S3, Kendra), MySQL, Airtable, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions.
  • Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zendesk to inform model development and enhance predictive accuracy.
  • Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative GenAI use cases and solutions.

AWSPythonSQLKerasMachine LearningMySQLNumpyData scienceREST APIPandas

Posted 8 days ago
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🔥 AI Research Scientist (Sequential Decision Making)
Posted 9 days ago

📍 USA, Canada, UK

🧭 Full-Time

💸 171169.0 - 200000.0 USD per year

🔍 Industrial Automation

🏢 Company: Phaidra👥 1-10💰 $25,000,000 Series A almost 3 years agoArtificial Intelligence (AI)Industrial AutomationMachine LearningInformation Technology

  • PhD in a technical field or equivalent practical experience, with demonstrated expertise in one of the following areas: Planning Reinforcement Learning Optimization
  • 1+ years of applied research experience.
  • Strong background in software engineering, with proficiency in Python and open-source ML libraries such as Keras, TensorFlow, PyTorch, scipy, scikit-learn, numpy, pandas, and ray.
  • Prior experience with research projects and contributions to open-source software.
  • Collaborate with other AI researchers on applied real-world problems to demonstrate algorithmic feasibility and enhance algorithmic capabilities.
  • Design and implement prediction and decision algorithms to control complex non-linear dynamic systems.
  • Develop and maintain a benchmarking platform for algorithmic performance evaluation and experimental design.
  • Clearly and efficiently report and present research findings and developments, both internally and externally, verbally and in writing.
  • Participate in and organize ambitious collaborative research projects.
  • Work with external collaborators and maintain relationships with relevant research labs and key individuals.
  • Mentor and guide Research Engineers to apply research findings and developments to industrial domains.

PythonKerasMachine LearningNumpyPyTorchAlgorithmsData StructuresPandasTensorflowCommunication SkillsAnalytical SkillsResearchSoftware Engineering

Posted 9 days ago
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🔥 ML Engineer - ComfyUI
Posted 10 days ago

📍 Canada

🧭 Full-Time

🔍 Software Development

🏢 Company: Nura Studios

  • Proven experience in developing and deploying diffusion-based image-generation pipelines.
  • Advanced proficiency in Python, with a strong portfolio of projects demonstrating expertise in ML and AI.
  • Extensive experience with ComfyUI, Automatic1111, diffusers library or other diffusion framework.
  • Deep understanding of machine learning principles, algorithms, and techniques, particularly in the context of image generation.
  • Design and Develop Diffusion-Based Pipelines: Create and optimize diffusion-based image-generation pipelines tailored for artists, ensuring high-quality and consistent outputs, using either ComfyUI,, Automatic1111 or custom Python code.
  • Integrate and Customize Tools: Leverage and customize tools such as ComfyUI, Automatic1111 or diffusers to meet the specific needs of our creative tool, ensuring seamless integration and usability.
  • Collaborate with Artists and Designers: Work closely with artists and designers to understand their workflow needs and translate these into effective AI-driven solutions.
  • Stay Current with Advancements: Continuously monitor and integrate the latest advancements in machine learning and image generation, ensuring our tools remain cutting-edge.
  • Community Engagement: Actively participate in ML and AI communities, contributing insights and staying informed about emerging trends and technologies.
  • Optimize Performance: Analyze and optimize the performance of image-generation models, ensuring efficiency and scalability in production environments.
  • Documentation and Training: Develop comprehensive documentation and training materials to support users in effectively utilizing the creative tool.
  • Troubleshoot and Support: Provide technical support and troubleshooting for any issues related to the image-generation pipelines, ensuring minimal downtime and maximum productivity for users.
  • Conduct Research and Development: Engage in R&D to explore new techniques and methodologies that can enhance the capabilities of our creative tool.
  • Collaborate with Development Teams: Work alongside other developers to ensure the seamless integration of AI workflows within the overall architecture of the creative tool.
  • User Feedback Integration: Gather and analyze user feedback to continuously improve the functionality and user experience of the creative tool.
  • Maintain Code Quality: Ensure high standards of code quality, including writing clean, maintainable code and conducting regular code reviews.

DockerPythonImage ProcessingKerasMachine LearningNumpyPyTorchAlgorithmsData StructuresTensorflowRESTful APIs

Posted 10 days ago
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🔥 Senior Software Engineer, AI
Posted 14 days ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B about 1 year agoArtificial Intelligence (AI)Document Management

  • 5+ years of engineering experience
  • Excitement for product-focused application of ML/AI - this will be a production-focused role
  • Exceptional technical proficiency with at least one programming language, particularly Python or TypeScript
  • Understanding of ML concepts like supervised/unsupervised/self-supervised learning, neural networks and deep learning
  • Understanding of modern ML/AI technologies, including natural language processing (NLP) and LLMs (e.g., GPT-3+, open source models, etc.), RAG architectures, and their applications
  • Be an essential technical contributor at a Series B company as it scales.
  • Play a leadership role on the end-to-end development of features, specifically in regards to making architectural decisions and trading off different approaches.
  • Bring a mindset of continuous improvement to your work.

AWSBackend DevelopmentGraphQLPostgreSQLPythonSoftware DevelopmentSQLData AnalysisFrontend DevelopmentKerasMachine LearningPyTorchSoftware ArchitectureTypeScriptAlgorithmsData engineeringREST APIReactTensorflowCI/CDDevOps

Posted 14 days ago
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🔥 Senior Machine Learning Engineer (Remote)
Posted 15 days ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: AuditBoard

  • 5+ years of hands-on experience in developing and deploying machine learning models
  • Ability to write scalable production-quality code
  • Proficiency in classical machine learning methods and familiarity with newer techniques like LLMs
  • Excellent programming skills in Python, Java, or similar languages
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, Hugging Face, Keras, MXNet, or scikit-learn.
  • Familiarity with search/information retrieval and ranking systems
  • Strong communication skills and the ability to work collaboratively
  • Analytically minded with a focus on metrics and evaluation
  • Build, ship, and own end-to-end product features like predictive analytics, automated risk assessments, intelligent data extraction, and personalized insights.
  • Work with engineers, designers, and product managers to create high-performing product features.
  • Design and implement AI solutions using classical ML methods and advanced techniques like LLMs
  • Write well-designed, maintainable, and testable code
  • Write clear and well-defined design documentation
  • Troubleshoot, debug and resolve software bugs
  • Be product-minded and think about the customer
  • Stay updated on AI/ML advancements and explore new techniques and tools.
  • Participate in an Agile software development life cycle
  • Work with Python, JavaScript, Node.JS, Docker, PostgreSQL, Kubernetes, etc

AWSDockerNode.jsPostgreSQLPythonSoftware DevelopmentSQLJavaJavascriptKerasKubernetesMachine LearningNumpyPyTorchAlgorithmsData StructuresTensorflowCommunication SkillsAnalytical SkillsAgile methodologiesRESTful APIsSoftware EngineeringData analytics

Posted 15 days ago
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🔥 VP of Applied AI
Posted 15 days ago

📍 United States of America

🧭 Full-Time

🔍 Insurance

🏢 Company: external

  • 15 years of experience in data science, applied AI/ML, and advanced analytics, with a proven track record of developing and executing AI strategies that drive significant business transformation and ROI.
  • 8 years in leadership roles, including team building, mentoring, and retention, demonstrating the ability to recruit, develop, and lead high-performing AI/ML teams.
  • Expertise in aligning AI initiatives with business goals, facilitating cross-functional collaboration, and integrating AI solutions into existing processes.
  • Expert-level proficiency in Python and SQL for data manipulation and querying.
  • Proven experience in designing, implementing, and managing robust MLOps pipelines for automated model training, validation, versioning, deployment, performance monitoring, and governance.
  • Proficiency in using machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras for model development and experimentation.
  • Experience with cloud-based AI services and tools, such as AWS SageMaker, Google AI Platform, and Azure Machine Learning, to streamline AI development and deployment.
  • Define, articulate, and champion a clear, actionable AI strategy and multi-year roadmap aligned with AmeriLife's business objectives.
  • Identify, evaluate, and prioritize AI opportunities across all business functions, focusing on initiatives that deliver competitive differentiation and quantifiable ROI.
  • Collaborate closely with executive leadership and business unit heads to secure buy-in, allocate resources, and ensure strategic alignment for all AI initiatives.
  • Facilitate cross-functional collaboration to integrate AI solutions seamlessly into business processes and drive organizational change.
  • Lead the full lifecycle of AI/ML solution development: from ideation and design through development, testing, deployment, and maintenance.
  • Recruit, build, mentor, and lead a high-caliber, cross-functional team comprising AI/ML engineers, data scientists, and AI product or project managers.
  • Cultivate a dynamic team culture centered on innovation, rapid iteration, collaboration, continuous learning, and ethical AI practices.
  • Forge strong partnerships with business units, especially core distribution channels, to co-create AI solutions that address specific needs and drive adoption.
  • Develop and execute comprehensive change management strategies to facilitate the smooth adoption of AI technologies.
  • Provide regular, transparent reporting on AI program progress, outcomes, and challenges to executive leadership and key stakeholders.
  • Utilize performance data and feedback loops to continuously refine the AI strategy, prioritize initiatives, and optimize deployed solutions.

AWSPythonSQLArtificial IntelligenceCloud ComputingKerasMachine LearningPyTorchData scienceTensorflowData modelingData analytics

Posted 15 days ago
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🔥 Principal MLOPs Engineer (Canada)
Posted 15 days ago

📍 Canada

🔍 Machine Learning

  • Proven track record in designing and implementing cost-effective and scalable ML inference systems.
  • Hands-on experience with leading deep learning frameworks such as TensorFlow, Keras, or Spark MLlib.
  • Solid foundation in machine learning algorithms, natural language processing, and statistical modeling.
  • Strong grasp of fundamental computer science concepts including algorithms, distributed systems, data structures, and database management.
  • Proficiency and recent experience in Java is required (Must have)
  • Proven experience in Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
  • Expertise in public cloud services, particularly in GCP and Vertex AI.
  • Proven expertise in applying model optimization techniques (distillation, quantization, hardware acceleration) to production environments.
  • Proficiency and recent experience in Java is required (Must have)
  • In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
  • Architect and optimize our existing data infrastructure to support cutting-edge machine learning and deep learning models.
  • Collaborate closely with cross-functional teams to translate business objectives into robust engineering solutions.
  • Own the end-to-end development and operation of high-performance, cost-effective inference systems for a diverse range of models, including state-of-the-art LLMs.
  • Provide technical leadership and mentorship to foster a high-performing engineering team.

PythonApache HadoopGCPJavaKerasKubernetesMachine LearningMLFlowAlgorithmsData StructuresSparkTensorflowCI/CDLinuxDevOps

Posted 15 days ago
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🔥 Machine Learning Principal Solutions Architect
Posted 15 days ago

📍 United States, Latin America, India

🧭 Full-Time

🔍 Software Development

🏢 Company: phData👥 501-1000💰 $2,499,997 Seed about 7 years agoInformation ServicesAnalyticsInformation Technology

  • 8+ years as a hands-on Solutions Architect, Data Scientist, or Software Engineer that has designed and implemented complex AI/ML platforms and solutions
  • 3+ years previous Consulting leadership experience leading projects, expanding customer relationships and ensuring delivery lead growth
  • 4-year Bachelor's degree in Computer Science or a related field
  • Experience deploying machine learning models in a production setting
  • Proven track record of account expansion, pre-sales, and proposal development
  • Experience leading cross-functional teams of engineers, data scientists, and architects
  • Deep expertise in AI/ML technologies and platforms (e.g., AWS, GCP, Azure, Databricks, Vertex AI, SageMaker)
  • Expertise in Python, Scala, Java, or another modern programming language
  • The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets
  • Development of APIs and web server applications (e.g. Flask, Django, Spring)
  • Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment
  • Excellent communication and interpersonal skills, with the ability to navigate complex client relationships
  • Architect end-to-end AI/ML solutions, ensuring scalability, performance, and alignment with customer requirements and goals
  • Lead a team of machine learning engineers and data scientists to build AI/ML platforms, pipelines, and products that meet customer requirements and expectations
  • Communicate business value and ROI of AI/ML solutions to both technical and non-technical stakeholders
  • Mentor team members on best practices in AI/ML architecture, modeling, and technology.
  • Stay abreast of emerging technologies and methodologies in AI/ML to inform solution design and delivery.
  • Build relationships with client stakeholders to understand their long-term AI/ML goals and design roadmaps that align with business objectives.
  • Craft persuasive technical approaches and value propositions to drive client AI/ML initiatives forward
  • Identify and drive account expansion opportunities by uncovering unmet client needs and where AI/ML can add value.
  • Lead responses to RFIs and RFPs, crafting persuasive technical approaches and value propositions.

AWSBackend DevelopmentDockerLeadershipProject ManagementPythonSoftware DevelopmentSQLCloud ComputingDjangoFlaskFrontend DevelopmentGCPHadoopJavaKerasKubernetesMachine LearningMLFlowNumpySoftware ArchitectureSpringAPI testingAzureData scienceSparkTensorflowCommunication SkillsCI/CDAgile methodologiesRESTful APIsDevOpsAccount ManagementClient relationship managementSales experienceScalaTeam managementData modeling

Posted 15 days ago
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🔥 Senior Data Scientist
Posted 15 days ago

📍 United States

💸 120000.0 - 170000.0 USD per year

🔍 Insurance

🏢 Company: Verikai_External

  • Bachelor’s degree or above in Statistics, Mathematics, Actuarial Science or Computer Science with at least 5 years of relevant working experience
  • Possesses extensive expertise in machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning
  • Has in-depth knowledge of statistical analysis methods and their applications in data science
  • Skilled in optimizing data processing workflows to efficiently handle and analyze large amount of data
  • Demonstrates advanced proficiency in Python, with extensive experience in writing efficient, maintainable, and well-documented code
  • Has a working knowledge of PySpark, capable of performing basic data manipulation and processing tasks in a distributed computing environment
  • Experience of working on a cloud-based ML platform is a plus; Experience of working with insurance related data is a plus
  • Innovate and implement cutting-edge machine learning algorithms, aiming to extract greater lift from our data and deliver enhanced value to our customers
  • Proactively seek out and identify useful attributes from various data sources to enhance our core data assets. Rigorously validate the utility and relevance of new data to ensure it contributes to the improvement of our models and insights
  • Conduct thorough descriptive and statistical analyses on customer data to uncover valuable patterns and insights. Apply creative analytical approaches to ensure that results are directly aligned with customer needs and support their business decision-making processes
  • Present results, findings, and models to customers and stakeholders with a high level of technical expertise and industry knowledge. Act as a technical expert, industry insider, and company promoter, ensuing that presentations are clear, informative, and persuasive
  • Work closely with other data scientists, engineers, product managers, and other stakeholders to integrate machine learning models and statistical analyses into our products and services. Ensure seamless collaboration and knowledge sharing across the teams
  • Keep up with the latest developments and trends in machine learning, data science, and the insurance technology industry. Apply this knowledge to continuously improve our models, methodologies, and approaches
  • Adhere to data privacy regulations and ensure that all data handling practices comply with relevant legal and ethical standards. Maintain the highest levels of data security and confidentiality
  • Mentor and support the professional growth of the junior team members, fostering a culture of continuous learning and development

AWSPythonSQLCloud ComputingData AnalysisData MiningKerasMachine LearningNumpyAlgorithmsData sciencePandasTensorflowCommunication SkillsRESTful APIsData visualizationData modeling

Posted 15 days ago
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