Applied AI Scientist

About the Role

We are seeking a mid-level Applied AI Scientist dedicated to innovating and implementing advanced artificial intelligence solutions that solve tangible business and customer problems. This position involves leveraging AI research, machine learning experiments, and software engineering to develop scalable and impactful applications. Collaboration with cross-functional teams including ML engineers, data scientists, product managers, and cloud experts is key to transitioning research into production systems. Passion for applied AI and machine learning research to drive meaningful outcomes is essential.

Key Duties

• Design, research, and build sophisticated AI and machine learning models tailored for practical use cases.
• Convert new AI research outputs into business-relevant solutions.
• Experiment with a diverse set of AI methods such as deep learning, NLP, computer vision, and generative AI.
• Create and run experiments to assess novel algorithms, architectures, and AI techniques.
• Analyze complex datasets to uncover patterns and AI application opportunities.
• Develop predictive systems, recommendation engines, optimization tools, and AI-driven applications.
• Utilize large language models, foundation models, embeddings, retrieval-augmented generation, AI agents, and multimodal AI as applicable.
• Manage data preparation, feature extraction, training, tuning, evaluation, and model refinement processes.
• Partner with engineering teams to deploy AI prototypes into scalable production solutions.
• Build frameworks for model evaluation, benchmarking, and ongoing performance monitoring.
• Evaluate models on aspects like accuracy, scalability, latency, cost, and business impact.
• Effectively communicate AI insights and recommendations to both technical and non-technical stakeholders.
• Produce detailed technical documentation, research summaries, presentations, and specifications.
• Advocate responsible AI practices emphasizing fairness, explainability, privacy, security, transparency, and governance.
• Keep abreast of academic publications, industry trends, emerging AI technologies, and identify innovation opportunities.
• Contribute to continual improvements enhancing AI capability, research quality, engineering efficiency, and business value.

Essential Qualifications and Skills

• Proven experience in applied AI, machine learning, data science, or related technical disciplines.
• Proficiency in Python programming along with expertise in machine learning and scientific computing libraries.
• Solid understanding of machine learning theory, including algorithms, deep learning, statistical modeling, optimization, and experimental design.
• Experience using frameworks like PyTorch, TensorFlow, Scikit-learn, or Hugging Face.
• Hands-on experience creating and assessing AI models for practical environments.
• Knowledge of advanced AI concepts such as generative AI, large language models, prompt engineering, retrieval-augmented generation (RAG), AI agents, and multimodal AI is a plus.
• Familiarity with NLP, computer vision, recommendation systems, predictive analytics, or other applied AI areas preferred.
• Expertise in data preprocessing, feature engineering, model validation, and performance tuning.
• Experience managing large-scale datasets, both structured and unstructured, along with data pipelines and databases.
• Exposure to cloud environments like AWS, Azure, Google Cloud or similar platforms.
• Understanding of MLOps practices, including model deployment, continuous integration/continuous deployment (CI/CD), Docker, and Kubernetes is advantageous.
• Strong analytical, critical thinking, research aptitude, and problem-solving abilities.
• Excellent communication skills capable of clearly explaining complex AI research and concepts.
• Ability to collaborate effectively with interdisciplinary teams and translate research into actionable business applications.
• Intellectual curiosity, creativity, professionalism, adaptability, and eagerness for lifelong learning.
• Preferred academic credentials include Bachelor’s or Master’s degree in AI, Machine Learning, Computer Science, Data Science, Statistics, Mathematics, or related fields.
• PhD or substantial research exposure in AI or machine learning is advantageous.

Benefits and Opportunities

• A unique chance to apply forefront AI research to solve real business and customer challenges.
• Engagement with state-of-the-art AI technologies including generative AI, large language models, AI agents, computer vision, NLP, and multimodal AI.
• Contribution to innovative AI projects delivering measurable impact.
• Support for career advancement and professional growth in a dynamic technology landscape.
• Access to ongoing training, research mentorship, conferences, and certification support.
• Collaboration with a skilled team of AI scientists, engineers, and technology leaders.
• Availability of modern AI tools, cloud resources, and advanced computational platforms.
• Competitive remuneration and comprehensive benefits.
• A culture that encourages innovation, responsible AI, scientific inquiry, technical excellence, and continuous skill development.
• An impactful role helping transform cutting-edge AI research into practical solutions enhancing decision-making, automating complex processes, enriching customer experience, and shaping the future of AI.