Machine Learning Engineer

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AVAHI

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Social Impact • Non-profit • B2B

AVAHI is a consulting firm specialized in sustainable and inclusive development. It operates advocacy and awareness activities through a non-profit association and provides advisory services including impact studies, investment opportunity analyses, market studies, business plan development, fundraising support, training, mentoring, and workshop facilitation. AVAHI works across sectors such as education, renewable energy, circular economy, agribusiness and ICT, serving startups, SMEs, investment funds and development agencies to promote entrepreneurship, impact investment and progress toward the UN Sustainable Development Goals.

1 - 10 employees

Founded 2018

🌍 Social Impact

🤝 Non-profit

🤝 B2B

📋 Description

• Own the productionization of machine learning models, ensuring they meet performance, reliability, and maintainability standards before deployment • Establish and enforce best practices for code review, testing, version control, and documentation across ML projects • Collaborate closely with Data Scientists to understand model requirements and translate experimental code into production-grade implementations • Partner with Data Engineers to ensure feature pipelines, data transformations, and model inputs are well-architected and performant • Work with DevOps and platform teams to design and implement MLOps workflows including CI/CD, model monitoring, and automated retraining • Design and build ML infrastructure and pipelines on AWS using services such as SageMaker, Lambda, Step Functions, ECS/EKS, and related tooling • Implement model serving solutions that balance latency, cost, and scalability requirements • Participate in technical discussions with clients to understand requirements and communicate architectural decisions • Contribute to solution design and technical proposals • Mentor junior team members and help raise the technical bar across the organization

🎯 Requirements

• 3+ years of experience in software engineering, machine learning engineering, or a related field • Strong programming skills in Python with an emphasis on writing clean, testable, well-documented code • Hands-on experience deploying and maintaining ML models in production environments • Proficiency with AWS services, particularly those related to data and ML workloads • Solid understanding of ML fundamentals including model training, evaluation, feature engineering, and common algorithms • Experience with containerization (Docker) and orchestration tools • Familiarity with MLOps practices including experiment tracking, model versioning, CI/CD for ML, and monitoring • Strong communication skills and the ability to work effectively with cross-functional teams

🏖️ Benefits

• Competitive salary • Health insurance • Flexible work hours • Paid time off • Professional development