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🔥 Machine Learning Engineer Internship, WebML - EMEA Remote

Posted about 4 hours ago

📍 France

🧭 Internship

🔍 Machine Learning

🏢 Company: Hugging Face👥 51-200💰 $235,000,000 Series D over 1 year agoSoftware Development

🔧 Requirements

Interest in open-source, passion for making complex technology accessible, and a desire to contribute to a fast-growing ML ecosystem.

💡 Responsibilities

Converting and optimizing models for in-browser inference (ONNX, quantization)
Enabling models to run in-browser at near-native speeds (WebGPU, WebNN, WASM)
Building demo applications to showcase new features
Fostering a collaborative open-source community

Python Frontend Development Git Javascript Machine Learning Numpy OpenCV PyTorch React.js TypeScript Algorithms Data Structures REST API Tensorflow Web3.js CI/CD RESTful APIs NodeJS Software Engineering

Posted about 4 hours ago

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🔥 Senior Software Engineer, AI

Posted about 9 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 9 hours ago

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🔥 Senior Machine Learning Engineer

Posted about 9 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 9 hours ago

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🔥 Machine Learning Engineer (LLMs)

Posted about 10 hours ago

📍 Poland

🧭 Full-Time

💸 23500.0 - 35000.0 PLN per month

🔍 Education Technology

🏢 Company: Brainly👥 251-500💰 $80,000,000 Series D about 4 years ago🫂 Last layoff over 2 years agoEducation EdTech Communities E-Learning Apps Social Network Peer to Peer Software

🔧 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 10 hours ago

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🔥 Junior Full Stack AI Engineer

Posted about 13 hours ago

📍 Worldwide

🧭 Full-Time

🔍 AI

🏢 Company: Creai

🔧 Requirements

Proficiency in Python and Java or Scala; familiarity with machine learning frameworks like TensorFlow or PyTorch and data libraries like pandas and scikit-learn.
Hands-on experience with AWS, Google Cloud, or Azure and their machine learning toolsets.
Proven ability to tackle complex problems using data analytics and predictive modeling.
Strong verbal and written communication skills with a team-oriented mindset, capable of working effectively with cross-functional teams.
Keen scientific curiosity with a commitment to staying updated on industry trends and best practices.
Familiarity with data structures, data modeling, and software architecture principles.

💡 Responsibilities

Design, build, and maintain efficient machine learning models and full-stack solutions from prototype to production, optimizing performance, scalability, and cost.
Work closely with data scientists, software engineers, and product managers to integrate AI models into broader software systems, ensuring seamless functionality.
Analyze large datasets, develop predictive models, and apply advanced statistical techniques to address client-specific challenges.
Continuously improve existing systems and algorithms for speed, efficiency, and reliability.
Utilize cloud platforms (AWS, Google Cloud, Azure) to deploy and scale AI solutions, leveraging services that enhance performance and cost-effectiveness.
Stay informed about the latest AI and machine learning trends and technologies, ensuring that Creai remains competitive.
Document development processes and present technical results to technical and non-technical stakeholders.

AWS Python SQL Cloud Computing Data Analysis Full Stack Development Java Machine Learning PyTorch Software Architecture Azure Pandas Tensorflow Communication Skills RESTful APIs Scala Data modeling

Posted about 13 hours ago

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🔥 AI Engineer

Posted 1 day ago

📍 U.S.

🧭 Full-Time

💸 145000.0 - 198000.0 USD per year

🔍 Software Development

🏢 Company: Vizcom

🔧 Requirements

Experience working with 2D and 3D diffusion techniques.
Understanding of 3D data and AI to make it more accessible and practical.
Familiar with LLMs and can apply them to solve real problems for users.
Make systems that are efficient, scalable, and robust.
Build tools with the people using them in mind, ensuring that AI enhances their work rather than complicating it.

💡 Responsibilities

Advance systems for generating, refining, and enhancing content in 2D and 3D.
Use diffusion models to generate shapes and materials, ensuring outputs are consistent and useful for real-world design.
Build LLM-powered tools that help designers by automating repetitive tasks and providing thoughtful feedback.
Adapt AI systems to be fast, reliable, and easy to use in real-time workflows.
Ensure that 2D and 3D tools work together seamlessly, helping designers move easily between different types of projects.

Backend Development Python 3D Modeling - Rhino Artificial Intelligence Image Processing Kubernetes Machine Learning PyTorch Algorithms Data Structures Tensorflow Communication Skills Analytical Skills Problem Solving RESTful APIs JSON Software Engineering Data analytics Debugging

Posted 1 day ago

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🔥 Senior Machine Learning Engineer II

Posted 1 day ago

📍 India

🔍 Software Development

🏢 Company: Apollo.io👥 501-1000💰 $100,000,000 Series D over 1 year agoSoftware Development

🔧 Requirements

8+ years of experience building Machine Learning or AI systems
Experience deploying and managing machine learning models in the cloud
Experience working with fine tuning LLMs and prompt engineering
Strong analytical and problem-solving skills
Proven software engineering skills in production environment, primarily using Python
Experience with Machine Learning software tools and libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, etc.)

💡 Responsibilities

Design, build, evaluate, deploy and iterate on scalable Machine Learning systems
Understand the Machine Learning stack at Apollo and continuously improve it
Build systems that help Apollo personalize their users’ experience
Evaluate the performance of machine learning systems against business objectives
Develop and maintain scalable data pipelines that power our algorithms
Implement automated monitoring, alerting, self-healing (restartable/graceful failures) features while productionizing data & ML workflows
Write unit/integration tests and contribute to engineering wiki

Python SQL Apache Airflow Cloud Computing Data Analysis Keras Machine Learning MLFlow Numpy PyTorch Algorithms REST API Tensorflow Software Engineering

Posted 1 day ago

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🔥 Head of Applied AI

Posted 2 days ago

📍 United States

🔍 Life Sciences

🏢 Company: TetraScience👥 101-250💰 $80,000,000 Series B almost 4 years agoPharmaceutical Biotechnology Data Management Internet of Things Life Science Data Integration Software

🔧 Requirements

15+ years of hands on experience in building data engineering platform, and AI/ML solutions, with a substantial portion in life sciences
Proven ability to define and drive AI strategy within a life sciences organization
Proven track record of deploying AI models and Use cases in production, addressing real-world biological and other life science problems
Deep understanding of life sciences domains such as: Drug development pipelines, Assay / test method development areas such as HTS, DMPK etc., Regulatory and compliance framework
Experience in managing AI initiatives from concept to deployment
Proven track-record of success developing product strategy within a start-up environment
Strong knowledge of machine learning (ML) and artificial intelligence (AI) methods, including: Deep Learning (DL), Reinforcement Learning (RL), Natural Language Processing (NLP), Computational biology and statistical modeling
Proficiency in programming languages and tools such as Python, R, TensorFlow, PyTorch etc.
Significant experience with AWS, Services-Architecture and web-scale design patterns
Excellent communication skills to convey complex technical concepts to non-technical stakeholders
Experience in collaborating with external partners and customers
Ability to advocate and evangelize for AI initiatives internally and externally

💡 Responsibilities

Own, define, and execute the technical and product vision for Applied AI solutions
Support and advise executive leadership regarding technical and commercial feasibility
Identify business opportunities and develop AI-driven solutions
Understand the commercial impact of AI in life sciences (e.g., improving R&D efficiency, reducing costs, accelerating time-to-market)
Provide key inputs into technology evaluation and technology planning activities
Provide thought leadership and represent TetraScience at industry and technology conferences
Collaborate with the customers and productize solutions
Collaborate with cross functional teams to build and evangelize the solutions
Provide hands on technical leadership for the SAIL (Scientific AI Leadership) team

AWS Backend Development Leadership Project Management Python SQL Artificial Intelligence Cloud Computing Machine Learning Product Management PyTorch Software Architecture Cross-functional Team Leadership Data engineering Data science Tensorflow Communication Skills RESTful APIs Microservices Strategic thinking Data modeling

Posted 2 days ago

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🔥 Senior AI Architect

Posted 2 days ago

📍 United States

🧭 Full-Time

💸 118000.0 - 231000.0 USD per year

🔍 Software Development

🏢 Company: MongoDB👥 1001-5000💰 Post-IPO Equity about 7 years agoDatabase Open Source Cloud Computing SaaS Software

🔧 Requirements

5+ years of progressive hands-on experience in any of the following; solution architecture, enterprise architecture, data science, AI/ML and/or software development, including 2+ years of hands-on experience in designing, building, and delivering AI-powered solutions, with a deep focus on GenAI technologies
Demonstrated thought and technical leadership in AI/GenAI technologies with experience in presenting from conferences to the board room, you have the ability to influence AI strategy and advocate best practices at C-suite whilst hands on to demonstrate the value of your ideas
Experience of building cloud-native applications using modern methodologies, test-first development, CI/CD pipelines, and microservices architectures
Good understanding of LLM architectures, vectorisation, and experience in designing Retrieval-Augmented Generation (RAG) systems for real-time applications with hands-on experience in AI/ML frameworks and tools, for example, Llamaindex, Hugging Face, LangGraph, LangChain, Pydantic, Cursor, TensorFlow, and PyTorch
Experience with cloud AI services (AWS Bedrock, Azure AI, GCP Vertex AI)
Proficiency in at least one modern programming language (ideally Python), with experience in one other modern language a plus (e.g., Node.js, Java, C#)
Experience in deploying cutting-edge GenAI technologies and LLMs, driving innovation in high-uncertainty projects
Ability to connect AI solutions to business outcomes, driving measurable value through data-driven innovation and strategic technology integration
Strong communication and leadership skills, with the ability to inspire confidence, challenge assumptions, and influence executive stakeholders
Proven ability to lead agile teams, driving backlog grooming, sprint planning, and showcases in collaboration with Product Owners and cross-functional teams
Ability to work remotely with a willingness to travel (up to 20%) for high-impact, in-person customer engagements

💡 Responsibilities

Take an “AI First” mindset, leveraging the latest GenAI technologies and solution partners to design, prototype, and implement high-impact AI solutions that solve real customer problems and drive tangible business value
Jump into customer scenarios, understanding their use case, scoping effort in supporting customers and rapidly ideate what the solution should be, innovating quickly and demonstrating the value of our technology and services
Engage directly with C-suite customer stakeholders, addressing complex business challenges through AI concepts and solutions, ensuring alignment on solution design and delivery
Quickly build prototypes and proofs of concepts using GenAI-assisted development tools, showcasing the art of the possible to customers and iterating based on feedback
Own the end-to-end design and delivery of scalable AI architectures, from data pipelines to model deployment, ensuring performance, security, and scalability at every step
Write production-quality code in modern languages (e.g., Python, Node.js, Java) to build, fine-tune, and deploy RAG architectures, LLMs and AI models, using frameworks like LangChain, TensorFlow, PyTorch, and Hugging Face
Architect data pipelines and modern data layers using MongoDB Atlas Vector Search, enabling real-time, AI-driven applications
Provide authoritative technical direction to delivery teams, ensuring architectural consistency and high-quality AI solutions that align with customer objectives
Define scope, estimate effort, and deliver product increments that align with customer business priorities, ensuring high-velocity, outcome-focused delivery
Stay ahead of the curve by experimenting with emerging GenAI techniques, optimizing development processes, and driving the adoption of best practices in responsible AI
Contribute to ongoing development of a repository of reusable solution components, including reference architectures, GenAI blueprints, and AI-driven application modules, to accelerate delivery
Actively participate in the MongoDB and GenAI communities, sharing insights, driving best practices, and influencing the direction of AI-driven solutions

AWS Leadership Node.js Python Software Development Artificial Intelligence Cloud Computing Java Kubernetes Machine Learning MongoDB PyTorch Software Architecture Data science REST API Tensorflow Communication Skills CI/CD Agile methodologies DevOps Microservices

Posted 2 days ago

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🔥 Principal Machine Learning Engineer - Large Scale Embedding - (Remote - US)

Posted 2 days ago

📍 United States

🔍 Software Development

🏢 Company: Jobgether👥 11-50💰 $1,493,585 Seed about 2 years agoInternet

🔧 Requirements

15+ years of technical leadership experience in machine learning and AI.
Proven ability to lead ML initiatives and communicate complex ideas effectively to cross-functional teams.
Expertise in Graph Neural Networks, collaborative filtering, knowledge graphs, and recommendation systems.
Strong coding proficiency in Python, with experience in ML frameworks like PyTorch Geometric, DGL, TensorFlow, and scikit-learn.
Solid understanding of ML infrastructure components and libraries for efficient distributed training and inference.

💡 Responsibilities

Lead the design and architecture of multi-entity embedding generation using GNN and transformers.
Define the technical roadmap, working with cross-functional partners to align execution plans.
Develop and optimize large-scale graph-based machine learning pipelines for recommendation systems.
Ensure scalable and efficient architectures for processing complex, interconnected data.
Collaborate with internal teams to improve relevance metrics and extend the use of models in upstream functions.
Mentor and support the growth of your team while contributing to overall product strategy.

Python Machine Learning MLFlow PyTorch Algorithms Data Structures Tensorflow Data modeling

Posted 2 days ago

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