Full-Stack ML Engineer We are seeking a talented and motivated Applied AI / Full-Stack ML Engineer to join a high-pace, AI-driven environment. As part of our team, you’ll work at the intersection of machine learning and full-stack software development—turning models and research into robust, scalable systems that power real world products. This is a great opportunity for engineers who like to own end-to-end solutions and thrive in ambiguous, fast-moving settings.squadchamp.com

Key Responsibilities

• Design, build, and deploy AI-powered workflows and pipelines that support production systems at scale.
• Integrate machine learning models (including large language models, transformers, or other specialized architectures) into customer-facing applications, ensuring low latency, high throughput, and reliability.
• Develop scalable APIs, microservices, and connectors for integrating with external systems (e.g. via REST, GraphQL, webhooks).
• Lead the design of data ingestion, preprocessing, feature engineering, and training/serving pipelines.
• Monitor, debug, and optimize model performance, resource usage, system stability, and cost.
• Implement system components for model observability (metrics, logging, monitoring) and support continuous retraining or adaptation.
• Work with cross-functional teams (product, design, research) to translate business requirements into robust technical solutions.
• Mentorship: Assist junior engineers, contribute to best practices, and help grow a culture of technical excellence.
• Stay current with advances in ML/AI, tooling, and infrastructure, and propose improvements or innovations when appropriate.

Required Qualifications

• 0 to 5 years of industry experience in software development, with demonstrable exposure to AI/ML or data-intensive systems.
• Strong programming skills — e.g. Python is essential; experience with TypeScript, Java, Go, or similar is a plus.
• Hands-on experience building full-stack/web applications (frontend + backend) or APIs.
• Experience training, deploying, or integrating ML models in production — including data pipelines, model serving, inference engines, etc.
• Familiarity with infrastructure, containers, orchestration (Docker, Kubernetes), cloud platforms (AWS, GCP, Azure), and DevOps/CI-CD principles.
• Ability to think architecturally: design evolvable, modular, maintainable systems.
• Strong debugging, testing, and analytical skills.
• Good communication skills to interface with technical and non-technical stakeholders.
• Self-motivated, adaptable, and comfortable working in an early-stage or evolving setting.

Preferred / Nice-to-Have

• Experience with large language models (LLMs), transformer architectures, LangChain, Hugging Face, or related frameworks.
• Knowledge of vector databases, retrieval-augmented generation (RAG) systems, embeddings, and similarity search.
• Experience with model monitoring, drift detection, scaling inference, caching, and performance optimization.
• Understanding of compliance, privacy, or regulated domains (e.g. healthcare, finance).
• Prior startup or high-growth product engineering experience.
• Master’s or higher degree in computer science, AI/ML, or a related field.

What You’ll Get

• The chance to shape AI-powered products and infrastructure from the ground up.
• Ownership: autonomy and responsibility over features, architecture, and outcomes.
• Exposure to cutting-edge research and the latest AI/ML trends.
• A collaborative environment with engineers, researchers, and product thinkers.
• Competitive compensation, equity upside, and growth potential.
• Opportunities for mentoring, learning, and professional development.

Ideal Candidate Profile

We are looking for someone who can wear multiple hats: part software engineer, part ML engineer, part systems thinker. You should be comfortable operating under uncertainty, learning new tools and methods, and bridging research-level ideas with robust production systems. You enjoy end-to-end ownership — from prototype to deployment — and actively seek to improve performance, reliability, and maintainability. You appreciate collaboration, feedback, and iterative improvement.

This role offers an excellent platform to contribute to real-world AI systems, accelerate your growth, and leave your mark on high-impact products. If you’re excited by the challenge of bringing AI/ML from research into daily use, we’d love to hear from you.

At Crossing Hurdles, we believe in building technology that pushes boundaries and creates real change. Join a team where innovation meets purpose, and every engineer contributes to redefining the future of intelligent automation and applied AI solutions.If you want to apply for this job click on the apply button