Lead / Senior Machine Learning Engineer

About the RoleTkxel is seeking a Lead/Senior Machine Learning Engineer with advanced hands-on expertise across the Machine Learning spectrum—including classical ML, Time Series Analysis, Deep Learning, Computer Vision, NLP, and Agentic AI systems. In this strategic leadership role, you'll drive end-to-end development and deployment of innovative LLM and ML solutions, manage high-performing teams, and collaborate deeply with research and product leaders to transform state-of-the-art AI into business value.Key Responsibilities Lead, mentor, and inspire a cross-functional team of ML engineers, data scientists, and MLOps experts. Architect and oversee the lifecycle of advanced ML/LLM projects—from data acquisition, pre-processing, classical modeling, and deep learning to robust production deployment. Drive initiatives in Agentic AI, Time Series Forecasting, Computer Vision, and NLP, championing best practices for each domain. Collaborate closely across Research, Product, and Infrastructure teams to define objectives, timelines, and measurable success metrics. Set technical direction in large-scale model training, distributed systems, model optimization, and ML infrastructure design. Ensure adoption of MLOps best practices including experiment tracking, governance, CI/CD, automated testing, and model monitoring. Manage and optimize compute resources (GPU/TPU), budgets, and enforce responsible AI standards with a focus on security and compliance. Communicate technical visions, project milestones, risks, and insights to both technical and non-technical stakeholders with clarity and impact. Required Skills & Qualifications 5+ years hands-on experience in Machine Learning (including classical ML, time series, deep learning, NLP, and Computer Vision). Advanced knowledge of LLMs, Transformers, and modern deep learning architectures. Proven leadership managing and scaling teams delivering high-impact ML/LLM solutions. Extensive experience with frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face, DeepSpeed. Deep understanding of MLOps tools (MLflow, Kubeflow, Vertex AI) and cloud platforms (AWS, GCP, Azure). Demonstrated expertise in distributed training, GPU/TPU optimization, and agentic AI workflows. Strong coding skills. Comfortable optimizing pipelines and delivering proof-of-concepts to production. Track record of successful cross-functional collaboration and exceptional communication. Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. Preferred / Nice to Have Experience building, fine-tuning, or scaling foundation models/LLMs. Contributions to open-source ML/LLM frameworks or libraries. Demonstrated understanding of Responsible AI, bias mitigation, model interpretability, and fairness. Prior success in deploying time series, agentic AI, or computer vision systems at scale. Why Tkxel?Join a cutting-edge environment pushing the boundaries of applied AI, with global impact and an organizational culture deeply committed to innovation, collaboration, and continuous learning.