Senior AI/ML Engineer

This role is for one of the Weekday's clients

Min Experience: 5 years

JobType: full-time

We are looking for a high-impact AI/ML Engineer to lead the development and deployment of advanced machine learning solutions across vision, audio, and language modalities. You'll work as part of a fast-paced, results-driven AI & Analytics team, collaborating with data scientists, engineers, and product stakeholders to bring real-time, scalable AI systems to life. The ideal candidate combines deep technical expertise, strong product thinking, and hands-on experience with Computer Vision, Audio Intelligence, and Deep Learning.

Requirements

• Design, develop, and deploy ML models for multimodal use cases, including image/video, audio/speech, and natural language.
• Own the full ML lifecycledata ingestion, model training, experimentation, evaluation, deployment, and monitoring.
• Apply techniques like transfer learning, foundation models, or self-supervised learning as needed.
• Build scalable training pipelines and inference services using frameworks like PyTorch or TensorFlow.
• Work closely with MLOps, data engineering, and DevOps teams to productionize models using Docker, Kubernetes, or serverless solutions.
• Continuously monitor model performance and maintain retraining workflows to sustain accuracy.
• Stay current with cutting-edge research (e.g., generative AI, video understanding, audio embeddings) and integrate relevant advancements into production.
• Write clean, reusable, and well-documented code to support rapid experimentation and long-term platform growth.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 58+ years of experience in AI/ML engineering, including 3+ years of hands-on deep learning experience.

• Languages: Expert in Python; working knowledge of R or Java is a plus.
• ML/DL Frameworks: Proficient with PyTorch, TensorFlow, Scikit-learn, ONNX.
• Computer Vision: Experience in classification, object detection, OCR, segmentation, tracking (e.g., YOLO, Detectron2, OpenCV, MediaPipe).
• Audio AI: Experience with speech recognition, sound classification, and audio embeddings (e.g., Wav2Vec2, Whisper).
• Data Engineering: Proficient in Pandas, NumPy, SQL, and building robust data preprocessing pipelines.
• NLP/LLMs: Familiar with Transformers, BERT, LLAMA, and the Hugging Face ecosystem.
• Cloud & MLOps: Hands-on experience with AWS, GCP, or Azure; tools like MLflow, SageMaker, Vertex AI, or Azure ML.
• Deployment: Skilled in Docker, Kubernetes, RESTful APIs, and serverless inference.
• CI/CD & Pipelines: Experience with Git, DVC, Jenkins, Airflow, and ML pipeline automation.

• Strong analytical and systems-thinking abilities; can break down complex business problems into ML components.
• Excellent communication skills; able to explain technical concepts to non-technical stakeholders.
• Comfortable working cross-functionally with product, design, and engineering teams.
• Bias for action and iterative delivery with a focus on measurable impact.

• Machine Learning
• Deep Learning
• Python
• AI / Data Science