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Senior Machine Learning Engineer - Remote at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Senior Machine Learning Engineer - Remote. in . India. .. In this role, you will lead the development of advanced AI systems that integrate language, vision, and voice to power intelligent, agentic platforms. You will take ownership of the full ML lifecycle, from data pipelines and model training to deployment and monitoring, while mentoring junior engineers and collaborating across cross-functional teams. The position offers an exciting opportunity to work with cutting-edge technologies, optimize high-performance AI pipelines, and influence the future of multimodal AI systems. You will contribute directly to the creation of scalable, real-time AI solutions that have tangible impact on user experiences, all within a dynamic, innovation-focused environment.. . Accountabilities. Design, develop, and scale AI systems that handle voice, vision, and language in real time.. Lead the full ML lifecycle, including data engineering, model architecture, training, deployment, and monitoring.. Develop and optimize multimodal AI solutions, including speech-to-speech and reinforcement learning pipelines.. Build and enhance RAG pipelines for live grounding of LLMs and multimodal integration.. Collaborate with infrastructure and systems engineers to manage cloud, GPU clusters, edge deployment, and CI/CD pipelines.. Mentor and guide junior ML engineers, define best practices, and shape the technical roadmap.. Translate research and experimental ideas into production-ready AI innovations.. . Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.. 3+ years of experience working with production ML systems.. Strong proficiency in Python; solid understanding of data structures, algorithms, OS, and networking fundamentals.. Expertise in LLMs (architecture, fine-tuning, LoRA/PEFT/instruction tuning) and multimodal ML (text, vision, voice).. Hands-on experience in Voice AI (ASR, TTS, embeddings, latency optimization).. Experience with RAG pipelines, vector databases, and orchestration tools.. Strong foundation in reinforcement learning, continual learning, and policy optimization.. Proficiency with ML frameworks such as PyTorch, TensorFlow, and scikit-learn.. Familiarity with tools like HuggingFace, LangFlow, vLLM, CrewAI, LoRA frameworks.. Experience with distributed training, large-scale pipelines, and inference latency optimization.. Cloud deployment experience (AWS/GCP/Azure), containers, Kubernetes, and CI/CD.. Ownership mindset, high resilience, ability to thrive in a startup or fast-paced environment.. . Company Location: United States.