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Jobs(38,923)/AI Engineer Role(1,041)/sweedpos.com (7) - Senior ML/AI Engineer
sweedpos.com

sweedpos.com - Senior ML/AI Engineer

Remote - International1mo ago
RemoteSeniorLATAMArtificial IntelligenceE-commerceAI EngineerMachine Learning EngineerProduct MarketingMLOpsAirflowPrometheusGrafana

Requirements

• 5+ years of production engineering experience in machine learning, AI engineering, backend engineering. We are open to strong backend engineers who would like to switch to AI Engineering • Experience with LLMs, RAG systems, AI agents, or orchestration frameworks such as LangGraph or PydanticAI • Hands-on experience building and shipping production systems • Experience with modern AI/LLM ecosystems, agentic frameworks, or strong interest in transitioning into this space • Understanding of ML/AI system design, experimentation, and production deployment practices • Experience building APIs or backend services • Experience with data processing and analytics workflows • Familiarity with MLOps concepts, monitoring, CI/CD, logging, and production reliability • Ability to work in ambiguous environments and independently drive technical initiatives • Strong communication skills and comfort working cross-functionally across multiple teams • Experience with recommendation systems, personalization, marketing automation, or eCommerce products • Familiarity with Airflow, Trino, Grafana, Prometheus, or modern data stack tooling • Experience working in product companies or fast-moving startup environments • Strong software engineering fundamentals and system design skills • WHAT ELSE MATTERS • We value people who take ownership, ask questions, and actively improve the systems around them. • AI evolves extremely fast. We’re looking for people who enjoy learning, experimenting, and evolving alongside the industry. • PRODUCT MINDSET • We care about building useful products, not just technically impressive systems. • This role involves close collaboration across engineering, analytics, product, and business teams.

Benefits

• We believe AI can unlock massive value for our customers - from intelligent recommendations and personalized experiences to workflow automation and agentic product capabilities. • As our ML Engineer, you’ll help shape the foundation of our AI systems and influence how AI is integrated across the entire platform. • This is not a role where you’ll only optimize isolated models. You’ll work end-to-end: from ideation and experimentation to production deployment and real product impact. • We’re still early enough in our AI journey that your ideas, technical decisions, and product thinking will directly shape the future of the platform. • WHAT YOU’LL WORK ON • Build and productionize AI-powered product features across eCommerce, marketing, analytics, and customer workflows • Design and implement agentic AI systems and LLM-powered workflows • Develop, train, evaluate, and deploy machine learning models into production environments • Work across the full ML lifecycle: experimentation, feature engineering, model evaluation, deployment, monitoring, and iteration • Collaborate closely with product managers, backend engineers, analysts, and DevOps teams to bring AI systems into production • Design scalable APIs and inference services for AI-driven functionality • Improve and evolve our ML infrastructure, tooling, and AI-native development workflows • Rapidly prototype ideas, validate hypotheses, and iterate based on real-world feedback and business impact • Contribute to experimentation frameworks, A/B testing approaches, and production monitoring practices • Stay current with the latest developments in LLMs, agentic systems, generative AI, and applied machine learning • Salary in USD (B2B contract with a US company) • 100% remote — we’re a remote-first company • Flexible working hours • 20 paid vacation days per year • 12 holidays per year • 3 sick leave days • Medical insurance after probation • Equipment reimbursement (laptops, monitors, etc.) • Opportunity to work on cutting-edge AI initiatives with high ownership and real product impact • 1. Recruiter Call (up to 45 minutes) • 2. Technical Interview (up to 1 hour) • 3. Machine Learning System Design Interview (up to 1 hour) • 4. Final Interview (up to 1 hour)

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