AI/ML Solution Engineer

Job not on LinkedIn

🕒 February 25

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Logo of Dominion Digital

Dominion Digital

1 - 10 employees

🤝 B2B

📱 Media

B2B • Media

Dominion Digital is a digital agency that designs and builds visually striking, user-centered websites and applications, and provides branding, 3D rendering, and growth/content strategy services. They combine design and development to create photorealistic 3D assets, intuitive UI/UX, and scalable web experiences aimed at helping brands stand out and grow online. Dominion Digital serves business clients across regions (Europe and West Africa) and focuses on delivering creative digital solutions that drive results.

📋 Description

• Collaborate with clients to understand business needs and translate them into AI/ML-driven solutions. • Build, fine-tune, and integrate AI/ML models (LLMs, NLP, computer vision, deep learning, traditional ML). • Deliver applications that are reliable, intuitive, and built for long-term value. • Navigate emerging and rapidly changing AI/ML technologies and tools. • Adapt quickly, lead through change, and make confident decisions with limited information. • Recommend modern approaches and innovations in AI/ML. • Ask the right questions to uncover root causes and deliver solutions that solve the real problem. • Dig into data pipelines, model architectures, optimization techniques, and workflows that drive better outcomes. • Architect scalable, maintainable AI/ML solutions that go beyond one-off experiments. • Uphold security, data governance, and best practices in every deployment. • Monitor model performance, retrain when necessary, and implement CI/CD pipelines for continuous improvement. • Help others by guiding team members to elevate technical delivery and AI/ML literacy.

🎯 Requirements

• Proficiency in Python (required); Java, JavaScript, SQL/NoSQL, and data processing tools (NumPy, Pandas, PySpark). • Understanding of C++, R, Julia, Scala a plus. • Proven experience building and deploying LLM applications, developing agentic workflows, and applying advanced prompting and fine-tuning strategies. • Knowledge of ETL/ELT pipelines, familiarity with big data frameworks, data pipeline tools, SQL/NoSQL • Hands-on experience with model development, training, deployment, and maintenance. • Experience with Scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face, and modern architectures (CNNs, RNNs, Transformers). • Experience with CI/CD pipelines, experiment tracking, model monitoring, versioning, and building scalable ETL/data pipelines. • Experience with AWS, Azure, GCP cloud infrastructures. • Containerization and Automation (Docker, Kubernetes, Jenkins, GitHub Actions). • Solid foundations in linear algebra, calculus, probability/statistics; familiarity with responsible AI practices, ethics, bias, and governance a plus. • Excellent communication skills to engage both technical and non-technical stakeholders, with a collaborative, problem-solving mindset.

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