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🔥 Machine Learning Manager, China (Remote)

Posted 1 day 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 1 day ago

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🔥 Senior Machine Learning Engineer, LS Embedding

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 216700.0 - 303400.0 USD per year

🔍 Software Development

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

🔧 Requirements

5+ years of experience in machine learning engineering, with a strong focus on recommendation systems, representation learning, and deep learning.
Hands-on experience with Graph Neural Networks (GNNs), collaborative filtering, and large-scale embeddings.
Proficiency in Python and experience with ML frameworks such as PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, or JAX.
Strong understanding of graph theory, network science, and representation learning techniques.
Experience building distributed training and inference systems using ML infrastructure components (data parallelism, model pruning, inference optimization, etc.).
Ability to work in a fast-paced environment, balancing innovation with high-quality production deployment.
Strong communication skills and the ability to collaborate cross-functionally with engineers, researchers, and product teams.

💡 Responsibilities

Design and implement scalable, high-performance machine learning models using Graph Neural Networks (GNNs), transformers, and knowledge graph approaches.
Develop and optimize large-scale embedding generation pipelines for Reddit’s recommendation systems.
Collaborate with ML infrastructure teams to enable efficient distributed training (multi-GPU, model/data parallelism) and low-latency serving.
Work closely with cross-functional teams (Ads, Feed Ranking, Content Understanding) to integrate embeddings into various personalization and ranking systems.
Drive feature engineering efforts, identifying and curating expressive raw data to enhance model effectiveness.
Monitor, evaluate, and improve model performance using A/B testing, offline metrics, and real-time feedback loops.
Stay up-to-date with the latest research in GNNs, transformers, and representation learning, bringing new ideas into production.
Participate in code reviews, mentor junior engineers, and contribute to technical decision-making.

Python Data Analysis Keras Machine Learning MLFlow PyTorch Algorithms Data Structures Tensorflow A/B testing

Posted 1 day ago

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🔥 Senior Data Scientist - (Remote - US)

Posted 2 days ago

📍 United States

🔍 Software Development

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

🔧 Requirements

5+ years of experience in AI, machine learning, and data science with practical deployment experience.
Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and Keras.
Extensive experience with Kubernetes and Docker for containerized AI deployments.
Familiarity with cloud environments (AWS preferred) for AI model deployment.
Expertise in SQL and standard data manipulation techniques.
Experience with anomaly detection, ideally related to financial crime patterns.
Knowledge of MLOps, including model monitoring, retraining strategies, and production pipelines.
Experience with AI testing platforms (e.g., MLflow) and C++ is a plus.
A full-stack mindset, with the ability to build, deploy, and refine AI solutions in production.
Strong customer interaction skills and the ability to translate customer needs into technical solutions.
A Ph.D. or Master’s in Computer Science, Mathematics, Statistics, or a related field is preferred but not required.

💡 Responsibilities

Develop and deploy machine learning models to detect financial crime, focusing on anomaly detection.
Enhance and optimize data pipelines, incorporating customer feedback to improve detection accuracy.
Lead AI model governance, ensuring models are interpretable, scalable, and reliable for real-world deployment.
Collaborate closely with customers and stakeholders to translate feedback into technical improvements and product enhancements.
Apply MLOps best practices to ensure smooth production-ready AI implementations.
Provide mentorship and technical guidance to junior team members while remaining hands-on with model development.
Stay updated on the latest AI trends and financial crime detection methodologies, continually evolving the platform's capabilities.

AWS Docker Python SQL Keras Kubernetes Machine Learning MLFlow PyTorch C++Data science Tensorflow

Posted 2 days ago

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🔥 AI Learning Experience Designer

Posted 6 days ago

📍 United States, Canada, United Kingdom, Australia, Singapore

🧭 Contract

💸 45.0 - 55.0 USD per hour

🔍 Education

Python Artificial Intelligence Data Analysis Keras Machine Learning Numpy Data science Tensorflow

Posted 6 days ago

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🔥 Senior Data & AI Specialist

Posted 6 days ago

📍 Worldwide

🔍 Artificial Intelligence, Machine Learning

🏢 Company: NextMinder

🔧 Requirements

Bachelor's degree in Engineering, Economics, Mathematics, Physics, or related fields.
Minimum of 3 years of experience in Artificial Intelligence, Machine Learning, and data automation solutions.
Advanced proficiency in Python for data analysis, Generative AI, and Machine Learning.
Strong statistical foundation with high analytical and numerical capabilities.
Experience developing and deploying AI models in production.
Knowledge of structured and unstructured databases, including Advanced SQL, NoSQL, and vector databases for embeddings and information retrieval.
Expertise in AI architectures and tools, including:
Machine Learning Frameworks: TensorFlow (Keras), PyTorch
NLP & LLMs: OpenAI API, Hugging Face, LangChain
Retrieval-Augmented Generation (RAG) techniques for improved AI responses
Proficiency in data visualization tools and dashboard creation.
Intermediate Excel skills.

💡 Responsibilities

Design and improve AI models and behavioural simulations, ensuring accuracy and adaptability across different scenarios.
Implement and optimize autonomous AI agents for task automation and advanced insight generation.
Explore different Machine Learning and Generative AI approaches, including reinforcement learning, supervised learning, and unsupervised learning.
Apply fine-tuning and transfer learning to adapt models to diverse use cases.
Define and develop strategies for integrating AI into various products and business solutions.
Collaborate with product and engineering teams to translate AI capabilities into actionable functionalities.
Develop customization mechanisms to adapt AI models for different industries and customer needs.
Evaluate and define KPIs to measure and improve model performance
Design and execute data collection, processing, and validation strategies to enhance model accuracy.
Integrate Retrieval-Augmented Generation (RAG) techniques to ensure generated responses are contextually relevant and verifiable.
Apply predictive modeling and simulation techniques to anticipate trends and behaviors.
Validate model accuracy and consistency through comparisons with real data and reference models.
Implement dynamic adjustments and optimization of Language Models (LLMs) for improved adaptability across various contexts.
Work with technical teams to optimize data pipelines and ensure AI models are scalable and efficient in production.
Develop methodologies for the validation, updating, and continuous improvement of AI models.
Design interactive dashboards and reports to visualize trends, predictions, and AI model results.
Present findings and recommendations to key stakeholders, ensuring alignment with strategic business objectives.

Python SQL Artificial Intelligence Data Analysis Keras Machine Learning PyTorch Data science Nosql Tensorflow Communication Skills Analytical Skills Problem Solving Adaptability Data visualization Data modeling Data analytics

Posted 6 days ago

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🔥 Principal Product Manager, Multimodal & Vision AI

Posted 9 days ago

📍 United States

🧭 Full-Time

💸 186700.0 - 298300.0 USD per year

🔍 Software Development

🔧 Requirements

8+ years in a D2C/B2C product management role leading and testing AI products at scale (millions of customers), with at least 3+ years focused on multimodal AI systems spanning computer vision, natural language processing (NLP), and multi-modal fusion architectures.
Technical proficiency in modern AI approaches, encompassing: Previous involvement with foundational models, grasp of computer vision techniques (object detection, semantic segmentation, image classification), understanding of multimodal fusion methodologies for integrating data from various sources, knowledge of architecture supporting popular computer vision models, and awareness of Machine Learning Ops standard methodologies for large-scale AI systems.
Track Record of Shipping Complex ML/AI Products: Demonstrated success in bringing computer vision or multimodal AI products from conception to production at scale. Experience with model deployment, integration of complex data pipelines that handle multiple input modalities (images, text, sensor data, etc.), performance monitoring, and iterative improvement cycles.
Strong Product Sense in Solving in AI Applications: Ability record to translate raw technical capabilities into valuable, high-impact user experiences. Understanding of the possibilities and limitations of computer vision in a real customer context.
Cross-Functional Leadership in Technical Environments: Collaborate with ML engineers, scientists, designers to make technical trade-offs, aligning with customer vision.
Lead on 0 to 100 Products: Navigate ambiguity in a fast-paced setting, adapt to new technologies, apply rigorous learning and testing, and scale expertly.
Responsible AI Champion: Experience addressing ethical considerations such as bias detection and mitigation, privacy preservation, and compliance with relevant regulations.
Skilled communicator (both written and verbal) capable of explaining complex technical ideas to executive partners and technical audiences.

💡 Responsibilities

Spearhead the strategic innovation and integration of multimodal and computer vision AI technologies across Zillow's customer-facing experiences, balancing brand-new innovation with practical deployment.
Identify and complete key opportunities for creative customer experiences, developing innovative methods for buyers & renters to gain deeper insights into homes and locations.
Develop and evolve our multimodal AI roadmap, ensuring alignment with both technical feasibility and customer value.
Work closely with applied scientists, machine learning engineers, designers, and researchers to use Zillow's extensive real estate dataset for training models and developing experiences.
Translate complex technical capabilities into valuable, high-impact user experiences, focusing on visual, textual, and spatial data streams.
Lead cross-functional teams to deliver AI products from conception to production, ensuring robust model deployment, performance monitoring, and iterative improvements.
Drive responsible AI practices, addressing challenges around data privacy, bias mitigation, and fair housing compliance.
Stay informed about new technologies and industry trends to continuously push the team forward in innovative ways.

AWS Docker Python Data Analysis GCP Image Processing Keras Kubernetes Machine Learning Numpy Product Management PyTorch Cross-functional Team Leadership Product Development Product Analytics Algorithms Azure Data Structures REST API Pandas Tensorflow Communication Skills Analytical Skills CI/CD Problem Solving Strategic thinking

Posted 9 days ago

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🔥 Senior Full Stack AI Data Scientist

Posted 10 days ago

📍 United States

🏢 Company: MiTek👥 5001-10000 Civil Engineering Construction Enterprise Software

🔧 Requirements

5+ years of experience in computer vision, natural language processing, traditional machine learning, statistical analysis, or related domains required
Proficient in Python and SQL required
Proficient with machine learning, deep learning, and deployment frameworks such as TensorFlow, PyTorch, or Keras, Scikit-learn, Numpy, Pandas, OpenCV, Restful APIs, Docker required
Knowledge of statistical modeling and machine learning modeling required
Experience developing and deploying models and applications on cloud platforms such as Azure, AWS, or Google Cloud required
Excellent communication and presentation skills, with the ability to convey complex findings to non-technical stakeholders
Strong leadership and mentoring abilities
Strong business acumen and the ability to translate data insights into actionable recommendations

💡 Responsibilities

Research and implement state-of-the-art data science techniques for modeling and algorithm development.
Lead mid-size end-to-end projects using structured and unstructured data types, including time series data sources.
Manage and prioritize multiple projects, ensuring they are completed on time.
Create advanced data visualizations and dashboards to communicate effectively.
Collaborate with cross-functional teams of engineers, product managers, and researchers to deliver high-quality products and services.
Stay updated with the latest developments and trends in computer vision and artificial intelligence.
Attend meetings with customers and cross-functional departments to understand project needs and requirements, collect data sets, and assist with converting business requirements into technical specifications.
Develop POCs and prototypes (including data explorations) in a fast-paced environment to ensure feasibility, scalability, and accuracy of algorithms and models.
Educate and evangelize the use of AI among internal and external stakeholders.

AWS Docker Python SQL Cloud Computing Keras Machine Learning Numpy OpenCV PyTorch Algorithms Data science Pandas Tensorflow RESTful APIs Data visualization Data modeling

Posted 10 days ago

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🔥 Senior Cloud Engineer, ML Platform

Posted 12 days ago

📍 United States

🧭 Full-Time

💸 160000.0 - 200000.0 USD per year

🔍 Software Development

🏢 Company: GameChanger

🔧 Requirements

4+ years of hands-on cloud engineering experience with a focus on scaling ML/AI infrastructure in high-throughput, real-time environments.
Proficiency in Infrastructure-as-Code (Terraform, CloudFormation, or equivalent) to automate cloud infrastructure for ML systems.
Deep knowledge of AWS services, patterns and best practices for resiliency, scalability, and security.
Hands-on experience with container orchestration (e.g., Kubernetes, ECS) with a focus on solving real-world scalability challenges.

💡 Responsibilities

Architect and scale cloud-based infrastructure purpose-built for real-time and batch ML workloads, ensuring system efficiency and reliability.
Design model-serving infrastructure to handle high-throughput inference workloads, model versioning, and multi-model interactions.
Design observability strategies, ensuring model performance, system reliability, and infrastructure health are continuously monitored.
Collaborate with ML/DevOps/Backend/Security Engineers on projects, integrating new tools, improving deployment speeds, scalability, and resiliency to support their evolving roadmaps.

AWS Docker Python Apache Airflow Cloud Computing Git Keras Kubernetes Machine Learning MLFlow Numpy Algorithms API testing Data engineering Data Structures REST API Serverless Pandas Spark Tensorflow CI/CD Linux Terraform Microservices JSON

Posted 12 days ago

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🔥 Senior Machine Learning Engineer (Spain remote)

Posted 12 days ago

📍 Spain

🔍 Software Development

🔧 Requirements

Strong expertise in computer vision and deep learning.
Experience as a tech lead.

💡 Responsibilities

Develop the fastest, most accurate detection engine.
Work with state-of-the-art deep learning models and computer vision algorithms.
Help guide our technical strategy and mentor our talented engineers.

Docker Leadership Python Agile Git Image Processing Keras Kubernetes Machine Learning PyTorch SCRUM Algorithms Data Structures Tensorflow CI/CD RESTful APIs Mentoring Linux Data analytics

Posted 12 days ago

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🔥 Senior Software Engineer, AI

Posted 13 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

🔧 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.
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 13 days ago

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