- Company Name
- Solink
- Job Title
- Senior AI/ML Engineer
- Job Description
-
**Job Title:** Senior AI/ML Engineer
**Role Summary:**
Design, develop, and deploy production‑grade machine‑learning models—including computer‑vision, LLM/VLM, and multimodal solutions—for cloud and edge platforms. Own end‑to‑end ML features from proof‑of‑concept through integration, monitoring, and continuous improvement, delivering measurable value in high‑volume video analytics applications.
**Expectations:**
- 7+ years of experience building and shipping software with integrated ML components.
- Strong command of Python and major ML frameworks (PyTorch or TensorFlow).
- Proven ability to train, fine‑tune, optimize, and compress models for production.
- Hands‑on MLOps experience (data pipelines, experiment tracking, model serving, monitoring, retraining).
- Experience with cloud (AWS preferred) and/or edge/embedded deployments, understanding performance trade‑offs.
- Effective communicator able to translate complex ML concepts for technical and non‑technical stakeholders.
**Key Responsibilities:**
- Design, train, and deploy CV, LLM, VLM, and multimodal models on cloud and edge environments.
- Own ML‑driven features from experimentation to production, including instrumentation and performance tuning.
- Evaluate and integrate third‑party AI/LLM/VLM services, balancing cost and performance.
- Build and maintain MLOps pipelines (data prep, training, versioning, serving, monitoring).
- Collaborate with product and engineering teams to define model requirements and translate customer problems into predictive insights.
- Implement quality, observability, and alerting standards for AI services.
- Integrate ML components with backend and edge processing systems.
- Develop automated tests for both ML and software components.
- Troubleshoot production issues and drive architectural improvements.
- Stay current with advances in computer vision, generative AI, and applied ML.
**Required Skills:**
- Python (expert)
- PyTorch or TensorFlow
- Model training, fine‑tuning, distillation/compression
- MLOps tools (e.g., SageMaker, Flyte, Kubeflow, CI/CD)
- Cloud platforms, especially AWS (SageMaker, EC2, S3)
- Edge/embedded deployment (Ubuntu, AI accelerators, hardware constraints)
- Software engineering best practices (scalable code, testing, version control)
- Strong analytical and problem‑solving abilities
- Excellent written and verbal communication
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or related field (Master’s preferred).
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer) are a plus but not mandatory.