Junior ML Engineer (Computer Vision)

About the Role: Maximl's ML Engineering Team is looking to hire a Junior ML Engineer (Computer Vision) who can work with technical leadership within the team.

Key Responsibilities ·         Drive research & innovation
 Stay abreast of the latest academic and industry advances in computer vision, like

• object detection, segmentation, visual-language models, reasoning, OCR, video processing etc.—evaluate and integrate promising new techniques.

·         Prototype and validate new models
 Rapidly develop proof-of-concepts, run thorough A/B experiments, and establish robust evaluation benchmarks to de-risk technology choices before production.

·         Optimize for production at scale
 Lead efforts to compress, quantize, and accelerate models for cloud GPUs/TPUs and edge devices; integrate with CI/CD, automated testing, and containerized MLOps frameworks.

·         Mentor and coach engineers
 Provide technical leadership through code reviews, design reviews, brown-bag talks, and best-practice guidelines; help mid- and junior-level engineers grow their CV expertise and career.

·         Collaborate cross-functionally
 Work closely with product engineering teams, solution delivery, customer success and end customers to translate business requirements into technical specs, ensure data quality and availability, and deliver features that solve real customer safety-compliance problems.

·         Define and enforce coding standards
 Establish style guides, testing protocols, performance budgets, and documentation standards for CV projects; champion reproducibility and clean, well-documented code.

·         Lead technical architecture decisions
 Evaluate and select frameworks, libraries, annotation tools, and compute infrastructure; balance trade-offs between flexibility, performance, and cost.

·         Monitor and improve model performance
 Set up monitoring dashboards and alerting for model drift, accuracy regressions, and runtime failures; spearhead root-cause analyses and continuous retraining strategies.

• Drive research & innovation
• Prototype and validate new models
• Optimize for production at scale
• Mentor and coach engineers
• Collaborate cross-functionally
• Define and enforce coding standards
• Lead technical architecture decisions
• Monitor and improve model performance