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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Loka, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Cleansing, Data Distribution Service, Information Engineering, DevOps, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Search Technologies, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Backend, Containerization, Scikit Learn, Information Technology, HuggingFace, Machine Learning Operations - **Published:** August 24, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pecd2ck06w ## About the Role * Bachelor's degree in Computer Science or a related field. * 4+ years of AI/ML engineering experience. * Proven experience building GenAI solutions, prompt engineering, fine-tuning and serving LLMs, search and embeddings, and developing agents with common patterns (Agentic RAG, NLQ), using frameworks such as LangChain/LangGraph, LlamaIndex, smolagents and strands-agents. * Understanding of statistical, ML and deep learning algorithms. * Solid experience with cloud ML services, preferably AWS (Bedrock, AgentCore, SageMaker). * Experience with containerization and orchestration tools. * Client-facing experience. * Deep proficiency in Python and core ML libraries and frameworks (scikit-learn, PyTorch, HuggingFace, TensorFlow, Transformers). Leadership & Soft Skills * A track record of mentoring junior engineers and elevating team output. * Confidence leading client communications and managing expectations independently. * Autonomy, adaptability and a consistently positive presence on the teams you work with. Not Required but Nice to Have * MLOps/LLMOps experience, preferably in AWS, along with standard tooling (MLFlow, LangFuse). * Experience in consultancy environments or startups, including managing projects and adapting to different settings. Additional Requirements * Excellent English, as a global team, we work entirely in English for meetings, customer calls and business communications. * CV written in English. Personality Profile * Curious: You strive to learn and grow into different industries with a modern tech stack. * Autonomous and positive: You excel in a fully remote, globally distributed team. * Team player: You enjoy a collaborative approach. * Adaptable: You operate with a startup mindset and move at a startup pace. * Empathetic: You lead and mentor with patience and compassion. ## Description * Take full responsibility for assigned tasks and projects, ensuring accountability for outcomes and results. * Lead client communications, gathering requirements, managing expectations and communicating deliverables effectively. * Understand business objectives and build solutions that help achieve them, along with metrics to track progress. * Collaborate cross functionally with other teams (Data Engineering, DevOps, Backend) to ensure seamless integration of ML solutions. Technical Tasks * Design, build, and maintain generative AI systems end to end, developing LLM powered applications and agentic workflows, implementing RAG pipelines (data ingestion, chunking, embeddings, vector search). * Establish evaluation frameworks and production monitoring on your GenAI solutions to continuously measure output quality, accuracy, latency, cost, and reliability while iterating on prompts, models, and architecture. * Wrangle, explore and visualize data with a keen eye for data cleaning, as well as differences in data distribution that may affect post deployment performance. * Deploy, maintain and upgrade ML models and pipelines. * Analyze model errors and design strategies to overcome them. * Write and maintain technical documentation. * Drive architectural decisions and contribute to high level planning and strategy. * Continuously optimize solutions for performance, scalability and cost effectiveness, especially within the AWS environment. Internal Initiatives * Follow Loka's career track for growth by demonstrating technical excellence, innovation, autonomy, ownership, communication and teamwork. * Stay updated with industry trends and incorporate cutting edge techniques and tools into projects. Mentoring & Leadership * Serve as the primary ML specialist across multiple projects, elevating the team's work. * Provide guidance and mentorship to junior ML engineers within the team. ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)