Best AI tools for< Ml Operations Engineer >

Union.ai is an infrastructure platform designed for AI, ML, and data workloads. It offers a scalable MLOps platform that optimizes resources, reduces costs, and fosters collaboration among team members. Union.ai provides features such as declarative infrastructure, data lineage tracking, accelerated datasets, and more to streamline AI orchestration on Kubernetes. It aims to simplify the management of AI, ML, and data workflows in production environments by addressing complexities and offering cost-effective strategies.

Bloosk AI is an advanced AI tool designed to help businesses with tech transformation, AI and ML product management, data analytics, visualization, predictive analytics, and more. It offers a wide range of features and advantages to streamline operations and enhance decision-making processes. With a focus on AI and ML engineering, architecture, and user experience, Bloosk AI aims to empower organizations to leverage the power of artificial intelligence for improved performance and productivity.

Saal.ai is an AI company based in Abu Dhabi that offers innovative cognitive AI solutions for various industries such as healthcare, finance, and smart cities. The company leverages artificial intelligence to develop cognitive solutions, products, and platforms that help businesses automate their operations and address challenges using advanced AI technologies. Saal.ai's framework is flexible and continuously optimized to seamlessly integrate into any business, unlocking exponential growth opportunities for humanity.

Neuraspace is an AI/ML solution that focuses on smarter space traffic management. It automates risk assessment, provides maneuver suggestions, and reduces the time and manpower required for collision avoidance in low earth orbit. Neuraspace helps satellite operators, insurance carriers, regulators, and partners by streamlining operations, protecting fleets from collisions, and ensuring space safety and profitability. The AI tool offers scalable solutions to handle collision alerts, minimize unnecessary maneuvers, optimize space operations, and save fuel and money.

Tribe AI is a modern consultancy specializing in AI, data, and machine learning, helping organizations leverage artificial intelligence. The platform offers bespoke AI solutions, advisory services, and GenAI acceleration to unlock the potential of cutting-edge technology. Tribe AI connects top AI talent with companies across various industries, such as healthcare, venture capital, insurance, private equity, and technology, to optimize operations and drive innovation. The platform also features a network of experienced AI researchers, data scientists, ML engineers, and AI fairness experts, ensuring high-quality and secure AI solutions for clients.

illbeback.ai is the #1 site for AI jobs around the world. It provides a platform for both job seekers and employers to connect in the field of Artificial Intelligence. The website features a wide range of AI job listings from top companies, offering opportunities for professionals in the AI industry to advance their careers. With a user-friendly interface, illbeback.ai simplifies the job search process for AI enthusiasts and provides valuable resources for companies looking to hire AI talent.

Globose Technology Solutions Pvt Ltd (GTS) is an AI data collection company that provides various datasets such as image datasets, video datasets, text datasets, speech datasets, etc., to train machine learning models. They offer premium data collection services with a human touch, aiming to refine AI vision and propel AI forward. With over 25+ years of experience, they specialize in data management, annotation, and effective data collection techniques for AI/ML. The company focuses on unlocking high-quality data, understanding AI's transformative impact, and ensuring data accuracy as the backbone of reliable AI.

Space-O Technologies is a top-rated Artificial Intelligence Development Company with 14+ years of expertise in AI software development, consulting services, and ML development services. They excel in deep learning, NLP, computer vision, and AutoML, serving both startups and enterprises. Using advanced tools like Python, TensorFlow, and PyTorch, they create scalable and secure AI products to optimize efficiency, drive revenue growth, and deliver sustained performance.

Striveworks is an AI application that offers a Machine Learning Operations Platform designed to help organizations build, deploy, maintain, monitor, and audit machine learning models efficiently. It provides features such as rapid model deployment, data and model auditability, low-code interface, flexible deployment options, and operationalizing AI data science with real returns. Striveworks aims to accelerate the ML lifecycle, save time and money in model creation, and enable non-experts to leverage AI for data-driven decisions.

Seldon is an MLOps platform that helps enterprises deploy, monitor, and manage machine learning models at scale. It provides a range of features to help organizations accelerate model deployment, optimize infrastructure resource allocation, and manage models and risk. Seldon is trusted by the world's leading MLOps teams and has been used to install and manage over 10 million ML models. With Seldon, organizations can reduce deployment time from months to minutes, increase efficiency, and reduce infrastructure and cloud costs.

Protect AI is a comprehensive platform designed to secure AI systems by providing visibility and manageability to detect and mitigate unique AI security threats. The platform empowers organizations to embrace a security-first approach to AI, offering solutions for AI Security Posture Management, ML model security enforcement, AI/ML supply chain vulnerability database, LLM security monitoring, and observability. Protect AI aims to safeguard AI applications and ML systems from potential vulnerabilities, enabling users to build, adopt, and deploy AI models confidently and at scale.

Cyguru is an all-in-one cloud-based AI Security Operation Center (SOC) that offers a comprehensive range of features for a robust and secure digital landscape. Its Security Operation Center is the cornerstone of its service domain, providing AI-Powered Attack Detection, Continuous Monitoring for Vulnerabilities and Misconfigurations, Compliance Assurance, SecPedia: Your Cybersecurity Knowledge Hub, and Advanced ML & AI Detection. Cyguru's AI-Powered Analyst promptly alerts users to any suspicious behavior or activity that demands attention, ensuring timely delivery of notifications. The platform is accessible to everyone, with up to three free servers and subsequent pricing that is more than 85% below the industry average.

Data Zenith is a Kolkata-based startup specializing in innovative data analytics solutions. They offer tailored analytics services to help businesses unlock the potential of their data, streamline operations, and make informed decisions for sustainable growth. With a team of experienced data scientists, Data Zenith provides comprehensive data analysis, predictive analytics, and data visualization services to drive actionable insights and enhance operational efficiency.

Tektonic AI is an AI application that empowers businesses by providing AI agents to automate processes, make better decisions, and bridge data silos. It offers solutions to eliminate manual work, increase autonomy, streamline tasks, and close gaps between disconnected systems. The application is designed to enhance data quality, accelerate deal closures, optimize customer self-service, and ensure transparent operations. Tektonic AI is founded by industry veterans with expertise in AI, cloud, and enterprise software.

BigPanda is an AI-powered ITOps platform that helps businesses automatically identify actionable alerts, proactively prevent incidents, and ensure service availability. It uses advanced AI/ML algorithms to analyze large volumes of data from various sources, including monitoring tools, event logs, and ticketing systems. BigPanda's platform provides a unified view of IT operations, enabling teams to quickly identify and resolve issues before they impact business-critical services.

Wallaroo.AI is an AI inference platform that offers production-grade AI inference microservices optimized on OpenVINO for cloud and Edge AI application deployments on CPUs and GPUs. It provides hassle-free AI inferencing for any model, any hardware, anywhere, with ultrafast turnkey inference microservices. The platform enables users to deploy, manage, observe, and scale AI models effortlessly, reducing deployment costs and time-to-value significantly.

OptiSol is a global technology company offering digital transformation services to a diverse range of industries. With a team of over 400 professionals across 5 countries, OptiSol focuses on providing innovative IT solutions in areas such as AI, Cloud Computing, Digital Engineering, Quality Assurance, and Enterprise Services. The company prides itself on building strong partnerships with clients based on trust, transparency, and shared goals. OptiSol's services include AI & ML, Quality Engineering, Cloud Web Application, Gen AI Applications, Digital Engineering, Enterprise Solutions, User Experience Engineering, Mobile Application, and DevOps Automation.

Skim AI is a machine learning and artificial intelligence solution that provides custom AI and ML solutions to help businesses make better decisions. The platform offers services such as AI advisory, AI development, and AI as a service, catering to various industries from media to medical, content creation to crypto & blockchain. Skim AI aims to make AI and ML accessible to all sectors, even for those with limited knowledge in the field. The platform also offers training options for users who prefer to manage AI operations themselves.

Keylabs is a state-of-the-art data annotation platform that enhances AI projects with highly precise data annotation and innovative tools. It offers image and video annotation, labeling, and ML-assisted features for industries such as automotive, aerial, agriculture, robotics, manufacturing, waste management, medical, healthcare, retail, fashion, sports, security, livestock, construction, and logistics. Keylabs provides advanced annotation tools, built-in machine learning, efficient operation management, and extra high performance to boost the preparation of visual data for machine learning. The platform ensures transparency in pricing with no hidden fees and offers a free trial for users to experience its capabilities.

Functionize is an AI Agentic Automation Platform for Enterprises that offers expert AI agents to handle business processes autonomously. The platform utilizes deep learning neural networks to deliver unparalleled performance across various enterprise applications. Functionize's AI agents run autonomously, self-heal workflows, and redefine efficiency and reliability in automation. The platform provides immediate value with pretrained automation, evolves with operational environments, and ensures seamless adaptability and precision in every task. Functionize helps mitigate risks, unlock gains, and support digital transformation for enterprises.

ClearML Server is a backend service infrastructure for ClearML, facilitating collaboration and experiment management. It includes a web app, RESTful API, and file server for storing images and models. Users can deploy ClearML Server using Docker, AWS EC2 AMI, or Kubernetes. The system design supports single IP or sub-domain configurations with specific open ports. ClearML-Agent Services container allows launching long-lasting jobs and various use cases like auto-scaler service, controllers, optimizer, and applications. Advanced functionality includes web login authentication and non-responsive experiments watchdog. Upgrading ClearML Server involves stopping containers, backing up data, downloading the latest docker-compose.yml file, configuring ClearML-Agent Services, and spinning up docker containers. Community support is available through ClearML FAQ, Stack Overflow, GitHub issues, and email contact.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

Awesome AI & Data GitHub-Repos is a curated list of essential GitHub repositories covering the AI & ML landscape. It includes resources for Natural Language Processing, Large Language Models, Computer Vision, Data Science, Machine Learning, MLOps, Data Engineering, SQL & Database, and Statistics. The repository aims to provide a comprehensive collection of projects and resources for individuals studying or working in the field of AI and data science.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

The Python Redis Vector Library (RedisVL) is a tailor-made client for AI applications leveraging Redis. It enhances applications with Redis' speed, flexibility, and reliability, incorporating capabilities like vector-based semantic search, full-text search, and geo-spatial search. The library bridges the gap between the emerging AI-native developer ecosystem and the capabilities of Redis by providing a lightweight, elegant, and intuitive interface. It abstracts the features of Redis into a grammar that is more aligned to the needs of today's AI/ML Engineers or Data Scientists.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

The Prompt Engineering Holy Grail repository is a curated resource for prompt engineering enthusiasts, providing essential resources, tools, templates, and best practices to support learning and working in prompt engineering. It covers a wide range of topics related to prompt engineering, from beginner fundamentals to advanced techniques, and includes sections on learning resources, online courses, books, prompt generation tools, prompt management platforms, prompt testing and experimentation, prompt crafting libraries, prompt libraries and datasets, prompt engineering communities, freelance and job opportunities, contributing guidelines, code of conduct, support for the project, and contact information.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

Jina is a tool that allows users to build multimodal AI services and pipelines using cloud-native technologies. It provides a Pythonic experience for serving ML models and transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Users can build and serve models for any data type and deep learning framework, design high-performance services with easy scaling, serve LLM models while streaming their output, integrate with Docker containers via Executor Hub, and host on CPU/GPU using Jina AI Cloud. Jina also offers advanced orchestration and scaling capabilities, a smooth transition to the cloud, and easy scalability and concurrency features for applications. Users can deploy to their own cloud or system with Kubernetes and Docker Compose integration, and even deploy to JCloud for autoscaling and monitoring.

Hopsworks is a data platform for ML with a Python-centric Feature Store and MLOps capabilities. It provides collaboration for ML teams, offering a secure, governed platform for developing, managing, and sharing ML assets. Hopsworks supports project-based multi-tenancy, team collaboration, development tools for Data Science, and is available on any platform including managed cloud services and on-premise installations. The platform enables end-to-end responsibility from raw data to managed features and models, supports versioning, lineage, and provenance, and facilitates the complete MLOps life cycle.

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