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AI Engineer (Python, Machine Learning, Generative AI/LLMs) About Us Founded in 2011, Modus is a global, fully remote team of world-class technologists who thrive in a collaborative, innovative environment. We’re a digital product engineering partner for forward-thinking businesses. Our global teams work side-by-side with clients to design, build, and scale custom solutions that achieve real results and lasting change, partnering with industry leaders including AWS, GitHub, and Atlassian. We were fully remote before it was cool! Recognized as one of the Inc. 5000 Fastest Growing Private Companies for nine years and a top remote work company by FlexJobs, we have helped some of the world’s largest brands deliver powerful digital experiences. As an award-winning Atlassian partner with a world-class team, we help organizations innovate and solve complex challenges for Fortune 500 companies and beyond, we want to hear from you. Opportunity! We are looking for an AI Engineer to join our engineering team and design, build, and deploy intelligent solutions using modern Machine Learning, Deep Learning, and Generative AI technologies. You’ll work across the AI/ML lifecycle, from experimentation and model development to integration and production deployment, collaborating with engineering, product, and data teams to turn complex business challenges into scalable AI-powered solutions. Requirements: Strong proficiency in Python and experience developing production-ready AI/ML applications and services. Solid experience with Machine Learning , including model development, evaluation, optimization, and implementation. Hands-on experience building applications using Generative AI and Large Language Models (LLMs) . Experience with Deep Learning concepts, neural networks, and modern model architectures. Practical experience with PyTorch and/or TensorFlow . Experience with Natural Language Processing (NLP) , including areas such as text processing, embeddings, semantic search, classification, or generation. Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines and working with vector-based retrieval. Experience integrating AI/ML APIs, foundation models, and third-party AI services into applications. Understanding of MLOps and model deployment , including versioning, monitoring, CI/CD, and production ML workflows. Experience with data engineering concepts , including data preparation, transformation, pipelines, and storage for AI/ML workloads. Strong software engineering fundamentals with a focus on maintainability, scalability, testing, and code quality. Ability to collaborate effectively with engineers, data teams, product teams, and other stakeholders in a distributed environment. Bonus points: Experience with LLM fine-tuning, prompt engineering, and model evaluation . Experience with vector databases, embeddings, and semantic retrieval systems . Exposure to AI agents, tool/function calling, or multi-agent architectures . Experience with cloud-based AI/ML platforms, containerization, and orchestration technologies. Experience implementing AI observability, guardrails, responsible AI, or model governance . Experience optimizing AI applications for performance, latency, scalability, and cost . You’ll Love: Working on innovative AI-powered products with real-world scale and impact. Building intelligent experiences using modern Machine Learning and Generative AI technologies. Collaborating closely with engineering, product, and data teams to solve complex problems. Raising the bar for AI engineering standards, reliability, and responsible development practices. Exploring emerging AI technologies and continuously improving how intelligent solutions are built and delivered. By joining our team, you’ll be part of a winning squad that plays to each other’s strengths and celebrates every success together.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.