Numrah

Machine Learning Engineer 2026

Numrah is seeking a Machine Learning Engineer to design and implement ML solutions from ideation to production. The role involves fine-tuning and integrating LLMs, deploying and monitoring LLM-powered features at scale, and collaborating with engineering and product teams. The ideal candidate will write clean, scalable code, create detailed technical documentation, and stay current with the latest ML research, LLM capabilities, and MLOps best practices.

At Numrah, we build intelligent, modern applications that combine cutting-edge engineering with practical machine learning. We're looking for a Machine Learning Engineer who is deeply grounded in ML theory and excited to Design and implement ML solutions from ideation to production Fine-tune and integrate LLMs Deploy and monitor LLM-powered features at scale in real-world products Collaborate with engineers and product teams to build intelligent, user-facing features Write clean, scalable code and detailed technical documentation Stay current with the latest in ML research, LLM capabilities, and MLOps best practices<h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">What You’ll Do</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Design and implement ML solutions from ideation to production</li><li class="leading-relaxed">Fine-tune and integrate LLMs</li><li class="leading-relaxed">Deploy and monitor LLM-powered features at scale in real-world products</li><li class="leading-relaxed">Collaborate with engineers and product teams to build intelligent, user-facing features</li><li class="leading-relaxed">Write clean, scalable code and detailed technical documentation</li><li class="leading-relaxed">Stay current with the latest in ML research, LLM capabilities, and MLOps best practices</li></ul><h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">Must-Haves</h2>1. Be an Arabic speaker2. Have at least 1-2 year of non-internship experience in Machine Learning3. Strong ML and DL theory background, you don't just use things, you know how they are working under the hood.4. Production experience training and fine-tuning LLMs, with practical knowledge of transformer architectures in NLP applications.5. Experience with MLOps best practices.6. Collaborative mindset and ability to communicate technical ideas clearly<h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">Nice-to-Have</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Experience deploying LLM-based features to production</li><li class="leading-relaxed">Knowledge of parameter-efficient fine-tuning (LoRA, QLoRA, PEFT)</li><li class="leading-relaxed">Familiarity with RAG pipelines and vector databases (e.g., Pinecone, Weaviate)</li><li class="leading-relaxed">Understanding of model serving and inference optimization (quantization, batching)</li><li class="leading-relaxed">Exposure to MLOps practices (monitoring, versioning, CI/CD for ML)</li><li class="leading-relaxed">Experience with RESTful APIs, Docker, and cloud platforms (GCP, AWS, or Azure)</li><li class="leading-relaxed">Interest in NLP applications, smart assistants, or chatbot systems</li></ul>

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Crossover is the world's largest database of skilled remote talent (7 million users and counting!)We help amazing professionals all over the world prove that they're just as good as anyone in Silicon Valley—𝘢𝘯𝘥 𝘥𝘦𝘴𝘦𝘳𝘷𝘦 𝘵𝘩𝘦 𝘴𝘢𝘮𝘦 𝘱𝘢𝘺𝘤𝘩𝘦𝘤𝘬.Like the Olympics, it's hard to qualify... but it's worth it! Have you got what it takes to join the 5,000+ people from 130+ countries that we've recruited for high-paying full-time remote jobs?𝐇𝐄𝐋𝐏𝐅𝐔𝐋 𝐋𝐈𝐍𝐊𝐒: 🧑 Reviews from people we've hired: &nbsp; crossover.com/people-at-crossover 💼 Current openings: &nbsp; crossover.com/jobs 💎 Hire someone for your company: &nbsp; crossover.com/hire ♟️ How the process works: &nbsp; crossover.com/selection-process ❓ FAQs: &nbsp; crossover.com/help-and-faqs ~~~ 𝑵𝒐𝒕𝒆: Crossover jobs are are fully compliant with LinkedIn's policies, as well as the applicable laws in every country where we advertise.Allow us to clarify some common misconceptions: 1) The reason we post so many job ads is because LinkedIn organizes all job postings by location. So, the only way to reach candidates all over the world is to post multiple ads in every city you want to hire from. Most recruiters don't bother because it's too time consuming... but we're not most recruiters. 2) We mostly recruit independent contractors, not employees, because labor laws vary so much from one country to another that it's near-impossible to recruit globally otherwise (which is why it's still uncommon even though most jobs can now be done remotely). 3) As is standard for any self-employed person, the stated pay is the entire compensation package. Because they are not employees, each contractor is responsible for handling the things that an employer would take care of e.g. taxes, equipment, vacation time, health insurance. One of the major reasons that Crossover jobs pay so much more than local jobs is to overcompensate for these costs.It's hard, but it's worth it!

EVP Operations

<h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">Description</h2>Are you a product leader with a passion for innovation and a deep interest in AI? Do you enjoy working with cutting-edge products and being a front-runner in shaping your company’s strategic vision? If your answer to both is yes, then IgniteTech is looking for you.IgniteTech is changing the B2B enterprise software industry with a GenAI-first approach. We're looking for a leader who can revolutionize our product offerings with GenAI functionalities and skyrocket customer retention across a portfolio of 30+ products.At IgniteTech, you will get to apply your AI expertise across a broad range of enterprise software products and make a difference in the rapidly evolving tech landscape. You will work directly with the CEO to shape our GenAI-first strategy, defining use cases, developing product roadmaps, analyzing customer needs, and prioritizing enhancements.Seize the opportunity to join a company at the forefront of GenAI technology adoption, where your strategic influence and technical expertise can drive real-world impact. You will be part of a culture of excellence and growth, working in a dynamic environment that encourages exploration and diligence.If you are ready to take on this exciting challenge, apply now and join the GenAI revolution at IgniteTech.<h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">What you will be doing</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Building AI Opportunity Matrices – Create a structured matrix that ranks customer problems by AI feasibility, business value, and risk to guide go/no-go decisions and prioritize development efforts.</li><li class="leading-relaxed">Designing AI-Enhanced Product Roadmaps – Define and sequence product evolution from current state to AI-enabled futures, balancing quick wins with transformative features and clearly documenting dependencies and success metrics.</li><li class="leading-relaxed">Writing AI Feature Requirements – Translate AI capabilities into detailed user stories with acceptance criteria, performance benchmarks, and fallback behaviors to ensure a safe and usable AI product experience.</li><li class="leading-relaxed">Assessing Customer AI Readiness – Analyze customer segments to identify barriers to adoption, craft enablement plans, and recommend change management strategies that accelerate successful rollout of AI features.</li></ul><h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">What you will NOT be doing</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Dealing with bureaucratic constraints or micromanagement that hinder your creativity and autonomy</li><li class="leading-relaxed">Making technical decisions without considering the voice of the customer or the strategic vision of the company</li></ul><h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">Key responsibilities</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Enhancing product offerings with Generative AI functionalities to increase customer engagement and retention across the entire portfolio</li></ul><h2 class="text-2xl md:text-3xl font-bold mt-10 mb-4 border-b pb-2 text-gray-800">Candidate requirements</h2><ul class="list-disc list-inside my-5 pl-5 space-y-2 text-gray-700"><li class="leading-relaxed">Experiencing shipping at least 2 products or major features with AI/ML as a core component (not just prototypes or experiments)</li><li class="leading-relaxed">Experience managing a full product lifecycle — from concept to scale — for AI-enabled features/products</li><li class="leading-relaxed">Experience working with data science and ML engineering teams in a product leadership role</li></ul>

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This assessment gives us an idea of your C++ skills- Companies that evaluate this skillset in interviews: Rockstar Games, Ubisoft, Mayhem Studios, etc.- 10 Multiple Choice questions- Average time to complete: 7 to 10 minutes

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Machine Learning Engineer 2026

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