ML Engineering Manager

Role & responsibilities

Designation : ML engineer Manager

Job location : remote

Notice period : Only immediate joiners

What youll do

• Lead and inspire your team

  (AI engineers, platform engineers, and a product manager):
• Set clear goals, mentor team members, and foster a culture of impact, collaboration, and rapid learning.
• Implement agile processes that prioritize speed without sacrificing quality or security.

• Collaborate closely with customers

  to understand and address their AI safety challenges:
• Engage directly with customer teams to understand their innovation objectives, pain points, and safety requirements.
• Translate customer needs into actionable roadmaps aligned with their innovation cycles.

• Deliver tools and services

  that ensure AI applications are aligned, robust, interpretable, and safe:
• Oversee the development of platforms for alignment assessments, adversarial testing, drift detection, and interpretability analysis.
• Make informed build vs. buy decisions to optimize speed and customer integration.

• Champion engineering excellence

  in a high-stakes environment:
• Establish and enforce secure coding practices, automation, monitoring, and infrastructure-as-code.
• Ensure system reliability through defined SLAs, SLOs, rigorous testing, and clear operational dashboards.

• Continuously innovate

  within AI safety methodologies:
• Keep current with cutting-edge research in AI safety, adversarial testing, and model evaluation.
• Pilot emerging techniques that enhance our offerings and accelerate customer deployments.

Preferred candidate profile

Experiences you'll bring

• 5+ years of experience in software engineering, with at least 2 years managing technical teams or complex projects.
• Proven track record delivering AI, ML, or data-intensive platforms or services (e.g., model evaluation platforms, MLOps systems, AI safety tools).
• Demonstrated success in team leadership, coaching, and talent development.
• Excellent cross-functional collaboration and communication skills, bridging technical concepts with customer value.

Technical skills you'll need

• Proficiency with common software languages, frameworks, and tools such as Python, TensorFlow, PyTorch, Docker, Kubernetes, JavaScript, HTML/CSS, REST APIs, and SQL/noSQL databases
• Expertise with cloud environments such as AWS, GCP, or Azure.
• Familiarity with LLM architectures, including evaluation techniques, prompt engineering, and adversarial testing methodologies.

Preferred technical experience: exposure to platforms like LangChain, LangGraph; experience with distributed systems (Spark/Flink); familiarity with AI regulatory frameworks or secure deployment standards (e.g., SOC 2, ISO 27001).

Interested candidates can apply to kinnera259@gmail.com

Regards,

HR Manager