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222 jobs found.

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🔥 Data Scientist (Applied Machine Learning)

Posted about 1 hour ago

📍 Europe

🧭 Full-Time

🔍 Hospitality

🏢 Company: Nory

🔧 Requirements

A scientific approach to problem solving based on crafting and testing hypotheses
The ability to write clean and maintainable python code
Real world experience deploying algorithms into production
Strong fundamentals in ML theory
Familiarity with cloud infrastructure

💡 Responsibilities

Design, build and deploy production new machine learning algorithms
Monitor, maintain and iterate on existing algorithms
Work closely with product and engineering on collaborative feature releases
Contribute to the wider data and tech community at Nory

Python Cloud Computing Machine Learning MLFlow Numpy Algorithms Data science Data Structures Pandas RESTful APIs

Posted about 1 hour ago

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🔥 Senior AI Engineer

Posted about 4 hours ago

📍 Canada

🧭 Full-Time

🔍 Software Development

🏢 Company: Procurify👥 101-250💰 $20,000,000 5 months agoCloud Computing SaaS Supply Chain Management Enterprise Software FinTech Software Procurement

🔧 Requirements

4-6+ years in a similar Machine Learning or Data Scientist role, including 2+ years experience in LLMs.
Proven experience as the first ML engineer or a similar role, demonstrating a strong ability to build ML and AI systems from the ground up.
Demonstrated experience building AI apps in production.
Proficiency in machine learning frameworks and libraries (e.g. Tensorflow, PyTorch, scikit-learn, Pandas)
Experience in building with LLMs such as GPT, Claude, Llama etc and strong understanding of LLM architectures and tools (Llamaindex, vector databases, Transformers, Langchain etc)
Experience with ETL/ELT tools, Data Lakehouse tech (Databricks, Python, Apache Spark, Hive, Parquet) and advanced SQL knowledge.
Strong programming skills in Python and familiarity with additional languages and tools commonly used in ML engineering.
Comfortable leading by example and using influence to drive collaboration, documentation, and knowledge sharing across teams and with a broad range of stakeholders.
Able to demonstrate initiative, work independently, and thrive with autonomy while collaborating across teams in a culture of priority setting and moving forward with urgency in alignment with our organizational strategy
Adept at focusing on multiple competing priorities, solving unique and complex technical problems, and persistently resolving blockers to progress
Familiar with DevOps and MLOps principles such as design for manageability and root cause analysis
Familiar working within leading software development best practices such as scrum/kanban, CI/CD, and test automation
A strong driver to stay ahead of the curve with GenAI research and apply those insights to build real-world applications.

💡 Responsibilities

Develop and refine autonomous agents leveraging generative AI to automate and streamline user workflows, enhancing operational efficiency and user experience.
Design, create, evolve, and maintain scalable and efficient machine learning systems including, data pipelines, model training, deployment, and monitoring frameworks.
Integrate and leverage Large Language Models (LLMs) to develop advanced NLP features, including but not limited to chatbots, workflow automation agents and data analysis tools using state-of-the-art models (e.g. OpenAI, Anthropic, open source models).
Develop and enhance systems to deliver personalized experiences to our users, utilizing advanced machine learning and AI technologies to derive engagement and satisfaction.
Partner across Product and Engineering teams on requirements to create product capabilities that fundamentally rely on AI and Machine Learning.
Drive conversations within Engineering to improve and optimize the source data models, integration of the ML capabilities including those in our product platform.
Identify, design, and implement internal process improvements, including automation for data quality control and data validation, improved data delivery, and scalability.
Mentor other engineers, imparting best practices and institutionalizing efficient processes to foster growth and innovation within the team.

Python SQL ETL Machine Learning Numpy PyTorch Data engineering Data science Pandas Spark Tensorflow CI/CD RESTful APIs DevOps

Posted about 4 hours ago

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🔥 Data Scientist

Posted about 4 hours ago

📍 United States

🔍 Financial Information

🏢 Company: SmartAsset👥 251-500💰 Secondary Market over 3 years agoMarketplace Financial Services Personal Finance Wealth Management Finance FinTech

🔧 Requirements

Proficient in Python and SQL
Strong data visualization and analysis skills (pandas, numpy, matplotlib, scikit learn, tensorflow, etc)
Working experience with the development and deployment of predictive models, with an emphasis on time series and categorization models
Strong statistical foundation

💡 Responsibilities

Develop and deploy machine learning models that will drive business decisions and improve user experience
Utilize your strong problem-solving skills, programming know-how, and business analytics to solve real-world problems at scale
Access and analyze a variety of data to perform descriptive, predictive and prescriptive analytics, working closely with stakeholders from different teams (Sales, Marketing, Product, and Technology)
Be responsible for creating stable models that will run in a production environment

Python SQL Git Machine Learning Numpy Data science Pandas Tensorflow Data visualization

Posted about 4 hours ago

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🔥 Machine Learning Manager, China (Remote)

Posted about 15 hours ago

📍 China

🏢 Company: Bjak👥 101-250 Price Comparison InsurTech Information Technology

🔧 Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
Proven experience as an AI engineer or data scientist, with a track record of leading successful AI projects.
Proficiency in AI and machine learning frameworks and programming languages (e.g., Python).
Strong expertise in data preprocessing, feature engineering, and model evaluation.
Excellent problem-solving and critical-thinking skills.
Effective leadership, communication, and team management abilities.
A passion for staying at the forefront of AI and machine learning advancements.

💡 Responsibilities

Lead and mentor a team of AI engineers, providing technical guidance, coaching, and fostering their growth.
Collaborate with product managers and stakeholders to define AI project objectives, requirements, and timelines.
Design, develop, and implement AI models, algorithms, and applications to solve complex business challenges.
Oversee the end-to-end AI model lifecycle, including data collection, preprocessing, model training, evaluation, and deployment.
Stay updated with the latest advancements in AI and machine learning, incorporating best practices into projects.
Drive data-driven decision-making through advanced analytics and visualization techniques.
Ensure the security, scalability, and efficiency of AI solutions.
Lead research efforts to explore and integrate cutting-edge AI techniques.

Docker Python Artificial Intelligence Data Analysis Keras Machine Learning MLFlow Numpy Algorithms Apache Kafka API testing Data science REST API Pandas Spark Tensorflow CI/CD Microservices Data visualization Data modeling

Posted about 15 hours ago

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🔥 Senior AI Engineer

Posted about 21 hours ago

📍 India

🏢 Company: YipitData👥 251-500💰 Debt Financing 10 months agoMarket Research Analytics Data Visualization

🔧 Requirements

Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
Basic understanding of machine learning algorithms and deep learning models.
Hands-on experience with Python and AI frameworks (TensorFlow, PyTorch).
Familiarity with data processing libraries like Pandas, NumPy, and the regular expression.
Understanding of model evaluation techniques and performance metrics.

💡 Responsibilities

Assist in the development, training, and fine-tuning of machine learning (ML) models.
Design and implement data pipelines for training models on large-scale datasets, ensuring clean, high-quality, and diverse training data, and providing the ability for incremental learning.
Implement and optimize deep learning models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Support research and development of AI applications in natural language processing (NLP) and predictive analytics.
Be familiar with Docker & Kubernetes technology, and develop stable and model-integrated API services.
Experiment with prompt engineering, few-shot learning, and fine-tuning in LLM for various business use cases.
Optimize transformer-based models, LLM for efficiency, latency, and performance using quantization, pruning, and distillation techniques.

Docker Python Data Analysis Kubernetes Machine Learning Numpy PyTorch Algorithms Data engineering Pandas Tensorflow CI/CD RESTful APIs

Posted about 21 hours ago

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🔥 Senior AI Engineer

Posted 1 day ago

📍 São Paulo, Rio Grande do Sul, Rio de Janeiro, Belo Horizonte

🧭 Full-Time

🔍 Software Development

🔧 Requirements

Demonstrable experience in applied AI, with a foundation in machine learning, NLP, LLMs, and statistical analysis.
Strong understanding of the trade-offs between various generative AI models and the ability to choose the right model for specific use cases.
Experience with data embeddings and vector databases, understanding the trade-off between available options, and leveraging it to optimize data ingestion.
Experience in architecting and developing solutions that integrate generative AI with traditional software solutions with minimal to no oversight.
Experience building and testing a server-side platform for API development and orchestration.
Is proficient in the Python and Typescript language and understands the trade-offs between multiple frameworks and patterns.
Skilled in creating and adjusting prompts for complex AI systems to meet diverse project requirements.
Familiarity with testing and evaluating AI systems using state-of-the-art methods and best practices.
Hands-on experience deploying software on leading cloud platforms and utilizing AI tools like AWS Bedrock, Azure AI Services, and Vertex AI.
Strong collaboration skills and ability to work alongside developers from multiple different areas.
Ability to communicate complex AI solutions and concepts effectively to technical and non-technical stakeholders.

💡 Responsibilities

Apply your knowledge of AI systems and software engineering to develop solutions that directly address and resolve business problems.
Partner with professionals from Data Science and Data Engineering to address complex technical challenges, ensuring that the latest and most effective Data & AI techniques are being utilized.
Take ownership of implementing and optimizing applied AI components, ensuring they meet project needs with high complexity and scale.
Navigate and manipulate generative AI models, including (but not limited to) LLMs, to create prompts and solutions tailored to specific use cases.
Develop and incorporate AI solutions while adhering to industry best practices, including moderation, security, monitoring, and compliance standards.
Understand and properly apply Responsible AI concepts in all the stages of the solution.
Lead the charge in designing, measuring, and evaluating AI model outputs, developing standard and custom metrics to ensure alignment with business objectives.
Translate AI research and PoCs into production-ready features, delivering robust and scalable AI components that integrate seamlessly with larger systems.
Drive the selection and application of appropriate evaluation metrics, ensuring that AI solutions are robust, unbiased, and meet all necessary performance standards.

AWS Backend Development Docker Leadership Python SQL Artificial Intelligence Cloud Computing Data Analysis Git Kubernetes Machine Learning Numpy PyTorch Software Architecture TypeScript Algorithms API testing Data engineering Data science Data Structures REST API Serverless Pandas Tensorflow Communication Skills Analytical Skills Collaboration CI/CD Problem Solving Agile methodologies RESTful APIs Compliance JSON Data modeling Software Engineering Data management Debugging

Posted 1 day ago

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🔥 Solutions Architect, Conversational AI & Prompt Engineering

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 120000.0 - 200000.0 USD per year

🔍 Healthcare

🏢 Company: Qventus👥 101-250💰 $85,000,000 Series D 2 months agoArtificial Intelligence (AI)Machine Learning Hospital Analytics Health Care

🔧 Requirements

Familiarity with conversation modeling techniques, including state machines, decision trees, and graph-based models.
Experience with LLM-based conversational AI, such as GPT, Claude, Gemini, and LLaMA
Ability to use frameworks like Dialogflow, Rasa, Amazon Lex, Langchain, and others to implement conversational AI solutions.

💡 Responsibilities

Design and implement AI conversational flow logic, considering potential disruptions, multiple conversation turns, and alternate conversation paths to ensure interactions are effective and meet user and business goals.
Create and manage dialogue state, entity extraction, and intent recognition models.
Build a scalable and reusable chatbot logic system using a modular design approach

AWS Python SQL Artificial Intelligence Data Analysis GCP Machine Learning NLTK Numpy PyTorch TypeScript Algorithms Amazon Web Services API testing Data science REST API Nosql Tensorflow CI/CD Microservices JSON Data visualization CRM Data modeling NodeJS Software Engineering Data analytics Data management A/B testing

Posted 1 day ago

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🔥 Senior Data Scientist

Posted 1 day ago

📍 Germany, Austria

🏢 Company: Storyblok👥 101-250💰 $80,089,317 Series C 10 months agoInternet CMS IaaS Web Hosting Web Development PaaS Information Technology Web Design Software

🔧 Requirements

Proficiency in programming languages such as Python or R, and experience with SQL for data manipulation
Strong analytical and critical thinking skills with a keen attention to detail
Solid understanding of machine learning algorithms and experience applying them to real-world problems

💡 Responsibilities

Lead the development and implementation of advanced statistical and machine learning models to extract insights and drive business decisions
Collaborate with cross-functional teams to understand business challenges and develop data-driven solutions
Mentor and guide junior team members and Data Champions from other divisions, fostering a data-driven culture and enabling teams to leverage analytics effectively

AWS Python SQL Apache Airflow Cloud Computing Data Analysis Data Mining ETL GCP Machine Learning MLFlow Numpy Tableau Algorithms Azure Data engineering Data science Pandas Spark Tensorflow Communication Skills Data visualization Data modeling Data analytics A/B testing

Posted 1 day ago

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🔥 Team Lead Senior AI Engineer

Posted 2 days ago

📍 Poland, Romania, Ukraine

🔍 Cybersecurity

🏢 Company: Point Wild👥 101-250 Security Software

🔧 Requirements

Strong background in applied machine learning, inclusive of deep learning and natural language processing, with experience deploying AI in production.
Proficiency in Python, PyTorch/TensorFlow, and cloud-based ML deployment (AWS preferred).
Ability to translate AI capabilities into tangible product improvements that impact users.
Experience leading AI projects and mentoring engineers, with a track record of delivering AI-powered features in production.

💡 Responsibilities

Manage the execution of the AI roadmap, ensuring AI initiatives align with business objectives and drive measurable impact.
Partner with R&D teams across multiple product lines to scope, prioritize, and deliver AI-powered features and capabilities.
Serve as the single technical point of contact for AI initiatives, providing expert guidance on architecture, model selection, and deployment.
Write production-level code, submit PRs, and review team contributions—ensuring high-quality AI solutions with best practices in software engineering and MLOps.
Conduct PR reviews, uphold rigorous engineering standards, and mentor engineers to elevate AI development across the company.
Ensure AI solutions are deployable, maintainable, and optimized for real-world performance.

AWS Leadership Python SQL Artificial Intelligence Cloud Computing Machine Learning MLFlow Numpy PyTorch Algorithms Data Structures REST API Tensorflow Communication Skills Analytical Skills Problem Solving Mentoring Team management Software Engineering

Posted 2 days ago

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🔥 Distinguished Engineer - Machine Learning (VP level)

Posted 4 days ago

📍 Europe (incl. UK)

🧭 Full-Time

🔍 Software Development

🏢 Company: Axelera AI

🔧 Requirements

PhD in Computer Science, Machine Learning, Artificial Intelligence, or related fields.
10+ years of post-PhD experience in AI/ML research and development, with a track record of leading large-scale projects and driving impactful innovations outside of academia.
Deep expertise in AI/ML frameworks, deep learning algorithms, and hardware-optimized machine learning.
Strong background in neuromorphic computing, hardware-efficient AI, or computational neuroscience is a plus.
Experience managing and mentoring senior engineers, influencing company-wide technical direction, and driving engineering excellence.
Exceptional communication skills with the ability to influence executives, engineers, and external stakeholders.
A robust and continuous (incl. last 2 years) history of contributions to academic research, open-source projects, or industry consortiums is highly desirable.

💡 Responsibilities

Own and deliver company-wide AI and ML initiatives with multi-year, multi-team impact, ensuring scalability and adaptability beyond current business needs.
Provide thought leadership and influence Axelera AI’s strategic direction by engaging with senior leadership, external partners, and industry consortiums.
Lead the research and development of next-generation AI and ML models, driving significant breakthroughs in efficiency, performance, and innovation.
Spearhead engineering best practices, setting a high standard for system architecture, code quality, and team processes.
Actively contribute to hiring, mentoring, and coaching senior engineers, fostering a high-performance culture that attracts top talent.
Publish research findings, contribute to industry discussions, and represent Axelera AI at conferences and external engagements.
Bridge the gap between technical capabilities and business needs by collaborating with product and business teams to define roadmaps and strategic opportunities.
Lead large-scale, high-impact projects with exceptional execution, managing ambiguity, tight deadlines, and evolving requirements.
Drive continuous improvement by leveraging industry best practices, customer insights, and cutting-edge research to enhance Axelera AI's AI/ML solutions.
Foster a strong engineering community within Axelera AI by championing hybrid/remote-first collaboration practices, inclusion, and diversity initiatives.
Partner with executive leadership to define a long-term vision for AI and ML at Axelera AI, ensuring alignment with both market demands and technical advancements.
Develop scalable solutions and frameworks that empower multiple teams, enabling efficient ML deployment across Axelera AI’s product ecosystem.
Take ownership of technical decision-making, ensuring optimal solutions for the broader organization while driving innovation and calculated risk-taking.
Model a standard of excellence, accountability, and leadership that inspires teams and influences company-wide culture and strategy.

AWS Docker Leadership Project Management Python Artificial Intelligence Cloud Computing Data Analysis Data Mining Kubernetes Machine Learning Numpy OpenCV People Management PyTorch Software Architecture Cross-functional Team Leadership Product Development Algorithms Data science Data Structures REST API Strategic Management Tensorflow Communication Skills CI/CD Agile methodologies Mentoring Linux DevOps Research Data modeling Software Engineering

Posted 4 days ago

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