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Machine Learning

1,170 jobs found. to receive daily emails with new job openings that match your preferences.

1,170 jobs found.

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🔥 AI Specialist Auditor - Chemistry

Posted 43 minutes ago

📍 United States

🏢 Company: Wealth Recruitment, LLC

🔧 Requirements

Master’s degree, or PhD, in Chemistry or a related field.
Teaching experience (strong preference for educators and researchers).
Exceptional attention to detail and ability to spot inconsistencies.
Strong written and verbal communication skills in English.

💡 Responsibilities

Audit chemistry-related content used to train AI models.
Evaluate AI-generated responses for accuracy, clarity, and consistency.
Assess and refine prompts used for AI training.
Provide expert-level feedback to improve AI-generated content.
Work 40 hours per week (M-F, 8-hour days preferred).
Participate in 2-3 weekly meetings to discuss project goals and findings.

Artificial Intelligence Data Analysis Data Mining Machine Learning Algorithms Analytical Skills Attention to detail Written communication Problem-solving skills Research Verbal communication

Posted 43 minutes ago

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🔥 Data & AI Engineer (Frankfurt, Germany)

Posted about 4 hours ago

📍 Germany

🔍 AI and data analytics consulting

🏢 Company: Unit8 SA

🔧 Requirements

MSc level in the field of Computer Science, Machine Learning, Applied Statistics, Mathematics, or equivalent work experience.
Proficient software engineer who has experience in applying a blend of software engineering, machine learning, and statistical methods to solve real-world business problems
Proficient in one of the following languages: Python, Scala, Java.
Experience with cloud technologies is a strong plus.

💡 Responsibilities

Work with our customers to understand their challenges, design and implement solutions.
Closely collaborate with other data scientists, software engineers and business stakeholders.
Evaluate, compare and present results to technical and non-technical audience.
Contribute to the implementation and engineering of systems at different scales: from small proof-of-concepts to larger end-to-end data systems.
Implement best practices in CI/CD

AWS Docker Python SQL Cloud Computing Data Analysis ETL Java Kubernetes Machine Learning Algorithms Data engineering Data science Spark CI/CD RESTful APIs Scala Software Engineering

Posted about 4 hours ago

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🔥 Senior Software Engineer, AI

Posted about 5 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

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
Experience architecting systems and data pipelines that can handle the ingestion, digitalization, storage, and retrieval of document-heavy data sets, including document processing, search, and classification
Experience in developing, testing, evaluating and deploying ML models
Ability to collaborate on all aspects of product strategy and UX
Experience shaping an early stage tech stack and product, and engineering organization

💡 Responsibilities

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. You’ll be responsible for making our technology and processes better over time.
Understand how to optimize for iteration speed while maintaining a high quality bar and technical rigor.

AWS Backend Development GraphQL PostgreSQL Python SQL Artificial Intelligence Cloud Computing Data Analysis Data Mining Full Stack Development Git Keras Machine Learning Numpy PyTorch React.js Software Architecture TypeScript Data engineering REST API Pandas React Tensorflow CI/CD DevOps NodeJS Software Engineering

Posted about 5 hours ago

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🔥 Senior Platform Engineer, Machine Learning

Posted about 5 hours ago

📍 United States

🧭 Full-Time

🔍 Audit and advisory industry

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

3-4 years of experience in software engineering, DevOps, or related field with a focus on ML systems
Experience with ML frameworks
Experience with cloud platforms, preferably AWS
Experience with container runtime architectures, preferably Kubernetes
Proficiency with at least one programming language, preferably Python or Typescript
Familiarity with CI/CD practices and tools
Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation
Strong understanding of distributed systems and microservices architecture
Ability to work in a fast-paced, changing startup environment

💡 Responsibilities

Design and implement infrastructure for ML model management, including training, deployment, and monitoring
Build and maintain platforms for running ML algorithms at scale
Develop systems for A/B testing, performance monitoring, and continuous model training
Create and manage ETL infrastructure to support ML workflows
Implement best practices for MLOps, including version control for models and datasets
Collaborate with ML Engineers to optimize model performance and resource utilization
Ensure the scalability, reliability, and security of ML systems
Stay current with the latest advancements in MLOps and cloud technologies
Contribute to the development of internal tools and frameworks to improve ML workflow efficiency
Be an essential technical contributor at a Series B-stage company as it scales

AWS Docker Python Cloud Computing ETL Kubernetes Machine Learning CI/CD Terraform Microservices Software Engineering

Posted about 5 hours ago

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🔥 Senior Machine Learning Engineer

Posted about 5 hours ago

📍 USA

🧭 Full-Time

🔍 Audit and advisory

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

4-5 years of experience in applied machine learning or related field
Strong proficiency in Python and its ML/data science libraries
Extensive experience with NLP techniques and generative AI technologies
Experience with LLMs and both text-to-text and text-to-image generative models
Proficiency in working with large datasets and creating ETL processes
Experience with version control systems (e.g., Git) and CI/CD practices
Ability to work in a fast-paced, changing startup environment

💡 Responsibilities

Collaborate with stakeholders to identify and map business problems to ML solutions
Design, develop, and implement ML models with a focus on NLP and generative AI applications
Curate, clean, and prepare data for model development and training
Create and maintain ETL jobs for data processing
Conduct rapid prototyping of ML solutions to quickly iterate on ideas
Stay current with the latest advancements in ML, particularly in NLP and generative AI
Collaborate with the platform engineering team to integrate ML solutions into the overall product architecture
Implement data flywheels to continuously improve ML features through increased usage
Define and implement ML performance metrics
Contribute to the product roadmap with ML-driven feature ideas
Be an essential technical contributor at a Series B-stage company as it scales

AWS Python SQL ETL Git Machine Learning Numpy Data science Pandas Tensorflow CI/CD A/B testing

Posted about 5 hours ago

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🔥 AI & Automation Strategy Manager, Customer Support

Posted about 5 hours ago

📍 United States

🧭 Full-Time

💸 92000.0 - 120000.0 USD per year

🔍 Customer Support

🏢 Company: IPSY

🔧 Requirements

5+ years of experience managing self-service/knowledge management systems in a customer support environment
Experience with AI/ML implementations in customer service, from RFI to strategy and tools (and deep investments with vendors and technical partners)
Proven track record of implementing successful self-service strategies with measurable results
Strong technical project management experience with self-service technologies
Experience with data analysis and ability to translate insights into actionable improvements
Demonstrated success in cross-functional project leadership
Proficiency in project management tools (Asana, Jira) and analysis tools (Excel, PowerPoint)
Outstanding communication and stakeholder management skills
Experience with customer support operations and understanding of support metrics

💡 Responsibilities

Develop and execute a comprehensive self-service strategy that drives adoption while maintaining high CSAT scores
Lead the implementation and optimization of self-service technologies including knowledge bases, chatbots, and automated workflows
Build and maintain metrics dashboards to track self-service success rates, deflection rates, and cost savings
Partner with cross-functional stakeholders to ensure seamless integration of self-service solutions across all customer touchpoints
Identify opportunities to leverage AI/ML to enhance self-service capabilities
Drive continuous improvement through data analysis and customer feedback
Establish and monitor KPIs specific to self-service performance
Create and maintain documentation of processes, best practices, and standard operating procedures

Project Management Artificial Intelligence Business Intelligence Data Analysis Machine Learning Project Coordination Cross-functional Team Leadership Strategy Communication Skills Analytical Skills Customer service Data visualization Stakeholder management Data analytics Customer support Customer Success PowerPoint

Posted about 5 hours ago

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🔥 Machine Learning Engineer (LLMs)

Posted about 5 hours ago

📍 Poland

🧭 Full-Time

💸 23500.0 - 35000.0 PLN per month

🔍 Education Technology

🏢 Company: Brainly

🔧 Requirements

3+ years experience with deployment and maintenance of Machine Learning models in production
Experience in deploying and maintaining Deep Learning models, particularly Large Language Models (LLMs)
Strong command of writing production-level code in Python, with a focus on best engineering practices, in particular for training & deploying models.
PyData stack along with quick frontend frameworks e.g. streamlit.
Proven expertise in Cloud Computing (preferably AWS and services like IAM, EC2, S3, ECR, EKS, Redshift, Athena, Glue, Lambda, SecretManager) for storage, data pipelines, ML pipelines, and ML deployment.
Machine Learning frameworks such as: Tensorflow, PyTorch, JAX, scikit-learn, Transformers (HuggingFace).
Proven track record of development of data and machine learning pipelines.
Knowledge of Linux/Unix system, shell scripting.
Parallel computing (multi-processing, async, GPUs, types of AI parallelism).
Culture of DevOps and high-quality software standards.
Fluency in English.

💡 Responsibilities

Operationalization of Machine Learning Models
Orchestration of the entire ML model lifecycle, from development and deployment to monitoring, maintenance, and optimization ensuring scalability, efficiency, and reliability.
Implementation of automated workflows for model retraining, versioning, and performance tracking to ensure long-term stability.
Transformation of Machine Learning artifacts into production systems and services maintaining robust integration with existing engineering infrastructure.
Tooling, Infrastructure & Experimentation Support
Design and implementation of tools, frameworks, and infrastructure to enhance efficiency of Data Scientists and other stakeholders simplifying areas such as model training and evaluation, data annotation, and processing.
Working with large-scale datasets in structured and ad-hoc exploratory setups to support both creation of well-organized data pipelines and rapid experimentation and prototyping.
Supporting Technical Lead and Data Scientists in refactoring and optimizing research code, ensuring high-quality, reusability, and scalability of delivered solutions bridging the gap between AI experimentation and real-world deployment.
Continuous Learning
Staying up to date with cutting-edge advancements in AI technology, including state-of-the-art models, algorithms, tools, and frameworks (both models/algorithms and tools/libraries/SaaS/APIs, etc.).
Exploring opportunities to incorporate new methodologies, libraries, and services that enhance Brainly’s AI capabilities.

AWS Python SQL Bash Cloud Computing Kubernetes Machine Learning PyTorch Data science REST API Tensorflow CI/CD Linux DevOps Microservices

Posted about 5 hours ago

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🔥 Lead Machine Learning Scientist, Personalisation

Posted about 6 hours ago

📍 United Kingdom

🧭 Full-Time

💸 105000.0 - 140000.0 GBP per year

🔍 Financial Technology

🏢 Company: Monzo👥 1001-5000💰 Secondary Market 5 months ago🫂 Last layoff almost 5 years agoFinancial Services Banking Wealth Management FinTech

🔧 Requirements

Multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
Experience developing and shipping state of the art ML architectures to production and delivering business impact
Extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices

💡 Responsibilities

Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle business problems in personalisation.
Leading the design and development of advanced real time Machine Learning models, for example exploring how recent advances in machine learning (neural network, graph-based, and sequence-based architectures, LLMs) can drive improvements in our ability to deliver personalised user experiences.
Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.
Working closely with our ML platform team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.

Leadership Python SQL Cloud Computing Data Analysis Machine Learning Algorithms API testing Data science RESTful APIs Microservices Data modeling

Posted about 6 hours ago

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🔥 Product Marketer

Posted about 7 hours ago

📍 United States

🧭 Full-Time

🔍 Manufacturing

🏢 Company: Arch Systems👥 11-50💰 $4,500,000 over 1 year agoArtificial Intelligence (AI)Industrial Automation Internet of Things Predictive Analytics Machine Learning

🔧 Requirements

4+ years of hands-on product marketing experience in a B2B SaaS environment; preference is given to candidates with experience in the manufacturing or industrial technology sector.
Proven ability to translate complex technical concepts, particularly related to AI/ML and manufacturing technologies, into clear, concise, and compelling messaging for diverse audiences (e.g., technical users, business decision-makers, industry analysts).
Proficient in using various marketing software and tools, including CRM systems, marketing automation platforms (e.g., HubSpot), web and marketing analytics platforms (e.g., Google Analytics), sales enablement tools, project management software (Asana, Notion, etc), and content management systems.
Demonstrated ability to work effectively across functional teams (product, engineering, sales, customer success) and drive project completion.
Strong project management skills, including the ability to manage multiple projects simultaneously, prioritize effectively, and meet deadlines in a fast-paced environment.

💡 Responsibilities

Develop compelling product positioning and messaging that differentiates our AI-driven SaaS products in the competitive landscape and resonates with manufacturing industry stakeholders.
Empower the sales and customer success teams with the necessary tools and product training, including sales decks, case studies, battle cards, competitive analysis, product demos, and other sales collateral to drive sales success and accelerate deal cycles.
Design and execute data-driven go-to-market strategies for new product launches and feature releases, ensuring successful adoption and market penetration within target manufacturing segments.
Continuously monitor and analyze competitor products, industry trends, and market conditions within the manufacturing technology space.
Engage with customers to gather feedback, understand their pain points, and identify opportunities for customer advocacy.
Collaborate with the marketing content and design teams to create high-impact marketing materials, including blog posts, white papers, ebooks, webinars, website copy, sales collateral, customer knowledgebase articles, and other content assets to support marketing campaigns and drive lead generation.
Partner effectively with product management, sales, industry strategy, and customer success teams to ensure alignment in product development, marketing strategies, and go-to-market execution.

Project Management Data Analysis Machine Learning Salesforce Google Analytics Content creation Communication Skills Presentation skills Cross-functional collaboration Market Research Marketing CRM English communication SaaS

Posted about 7 hours ago

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🔥 Staff Product Manager (Insurance)

Posted about 7 hours ago

📍 United States

🧭 Full-Time

🔍 Insurtech

🏢 Company: NerdWallet

🔧 Requirements

10+ years in product management, preferably in Insurtech.
Proven track record of owning a product roadmap, leading products to success and driving significant business outcomes.
Strong ability to influence and build relationships across all levels of the organization and clearly articulate product ideas and strategies to both technical and non-technical audiences.
Proficient in using data analytics tools to derive actionable insights.
Ability to work closely with engineering teams and understand technical concepts especially driving product integrations with third party APIs.
Experience with regulatory frameworks related to insurance.
Experience with data science and machine learning is a plus.
Experience with SEO and performance marketing is a plus.

💡 Responsibilities

Leverage data and partner integrations to deliver Insurance solutions, aligning with the overall company vision.
Define and drive the strategy to build competitive and innovative insurance products that address customer needs.
Conduct market analysis and competitive research to identify trends, customer pain points, and opportunities for product growth.
Ensure that products are relevant and valuable to the target audience with a deep understanding of the financial profiles, goals, and challenges of expected consumers to drive product innovation and personalization.
Own product integrations with third party partners and NerdWallet clients.
Seamlessly execute on roadmaps for successful product launches and updates by partnering with data, engineering, marketing, and editorial teams to create and implement product roadmaps.
Lead product development projects from concept to launch, including defining requirements, setting timelines, and coordinating with stakeholders.
Live in the numbers: monitor and analyze product performance metrics, implement A/B tests and other optimization strategies to improve user engagement and conversion rates.
Stand in the shoes of our consumer: empathize with the audience we are building for and always bring consumer insights to the table.
Mentor and develop team members, fostering a culture of continuous improvement and innovation to ensure long-term success.

Leadership Project Management Data Analysis Machine Learning Product Management Product Operations Cross-functional Team Leadership Product Development Product Analytics API testing Communication Skills Analytical Skills Collaboration SEO Market Research Data visualization Stakeholder management Strategic thinking Data modeling Data analytics A/B testing

Posted about 7 hours ago

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