ML Engineer

Job Summary: We are seeking a highly technical and results-driven Machine Learning Engineer to design and build cutting-edge solutions for voice and text-based systems. Youll work on complex, unsolved problems using advanced ML techniques, with a strong focus on speech-native models, multimodal learning, and hardware optimization. If youre passionate about conversational AI, LLM-based virtual assistants, and real-world implementation, this role is for you. Job Responsibilities: Design and implement an end-to-end LLM-based conversational speech virtual assistant Benchmark and evaluate speech-native models (e.g., Moshi, SesameAI) for in-vehicle applications Fine-tune models for automotive domain adaptation Develop API frameworks for vehicle system control Optimize for Qualcomm SA8255P hardware platform Maintain and write Python code for audio preprocessing and integration Document model architectures, benchmarks, and optimization strategies Execute the full modeling lifecycle: data cleansing, feature engineering, and model selection Collaborate in an Agile Scrum team to prototype, build, and deploy real-world ML solutions Required Skills: 3+ years of hands-on ML experience in industry Deep knowledge of Voice2Voice architectures and speech-native models Experience with model quantization and edge-device optimization Strong audio processing expertise (feature extraction, acoustic modeling, noise handling) Proficiency with TensorFlow or PyTorch Solid understanding of ASR and TTS technologies, including transformer variants Experience with multimodal learning, attention mechanisms, and cross-modal fusion Familiarity with tools like TorchAudio and Librosa Hands-on experience fine-tuning transformer models using Huggingface, PyTorch/TensorFlow Experience with distributed training pipelines Background in algorithm design and complexity analysis Strong problem-solving, decision-making, and analytical skills Demonstrated ability to learn new technologies and collaborate across teams Proven track record of delivering high-impact, measurable outcomes Preferred Skills: Research experience in transformers or multimodal systems (academic or industry) Experience developing systems for in-vehicle applications Education: Not specified assumed Bachelors or masters in computer science, AI, or related field