Qureos Mentor

Navikenz

<div><p><b>Job Summary:
</b></p><p>We&rsquo;re looking for an experienced Senior DevOps Engineer who loves working with Kubernetes and AI-driven applications. In this role, you&rsquo;ll be responsible for designing, implementing, and maintaining scalable cloud infrastructure while supporting MLOps pipelines for AI workloads.</p><p><br>
<b>What You&rsquo;ll Be Doing:</b></p>
<div>
<ul><li>Building Scalable Infrastructure: You&rsquo;ll design, implement, and maintain cloud infrastructure using Kubernetes to handle AI and non-AI workloads efficiently.</li></ul>
<ul><li>Developing CI/CD &amp; MLOps Pipelines: Help us automate AI/ML workflows using tools like Kubeflow, MLflow, or Argo Workflows, ensuring seamless deployment and monitoring of AI models.</li></ul>
<ul><li>Optimizing AI Model Deployments: Work with ML engineers to fine-tune LLM models, AI-driven applications, and containerized environments for smooth operation.</li></ul>
<ul><li>Monitoring &amp; Performance Tuning: Keep an eye on Kubernetes clusters and AI workloads, using tools like Prometheus, Grafana, and Loki to ensure high availability and performance.</li></ul>
<ul><li>Automating Everything: Whether it&rsquo;s infrastructure provisioning (Terraform, Helm) or Kubernetes security best practices, you&rsquo;ll help enforce efficiency and compliance.</li></ul>
</div>
<p><b>Staying Ahead of the Curve:</b> You&rsquo;ll have the opportunity to explore and implement emerging AI infrastructure trends, including KServe, Ray, and Triton Inference Server.</p>
<p><b>
What We&rsquo;re Looking For:</b></p>
<div>
<ul><li>8+ years of experience in DevOps, SRE, or Platform Engineering role, with expertise in Kubernetes and cloud-native DevOps</li></ul>
<ul><li>Strong knowledge of Kubernetes fundamentals (deployments, services, ingress, storage, GPU scheduling, multi-cluster management).</li></ul>
<ul><li>Proficiency in scripting &amp; automation with Python, Bash, or Go, particularly for AI-related workflows.</li></ul>
<ul><li>Hands-on experience with AWS, Azure, or GCP, especially in Kubernetes-based AI/ML infrastructure (e.g., Amazon SageMaker, GKE with AI, Azure ML).</li></ul>
<ul><li>Hands-on experience with model deployment frameworks (NVIDIA Triton, vLLM. TGI etc.)</li></ul>
<ul><li>Experience with Distributed computing, multi-GPU training on kubernetes and on-prem GPU clusters.</li></ul>
<ul><li>Experience managing resource allocation and autoscaling for large training/inference workloads. (KEDA, HPA etc.)</li></ul>
<ul><li>Experience with CI/CD &amp; MLOps tools such as Jenkins, Argo CD, Kubeflow, MLflow, or Tekton.</li></ul>
<ul><li>Familiarity with GenAI model deployment, including fine-tuning, inference optimization, and A/B testing.</li></ul>
<ul><li>Hands-on experience with managed ML services (AWS bedrock, Vertext AI models etc.)</li></ul>
<ul><li>Strong problem-solving skills and a mindset of automating repetitive tasks.</li></ul>
<ul><li>Excellent communication skills to collaborate with ML engineers, data scientists, and software teams.</li></ul>
</div>
<p><b>Bonus Points If You Have:</b></p>
<div>
<ul><li>Experience with LLMOps (Large Language Model Operations) and deploying LLM-based applications at scale.</li></ul>
<ul><li>Knowledge of Vector Databases (FAISS, Weaviate, Qdrant) for AI-driven applications.</li></ul></div></div>

Senior DevOps Engineer (Kubernetes & AI Infra)

<div><p><b>Key Responsibilities:</b></p>
<ul>
<li>Design, develop, and deploy advanced Machine Learning and Deep Learning models for business-critical use cases.</li>
<li>Build and optimize Computer Vision pipelines using models like YOLO, EfficientNet, or Transformer-based vision architectures.</li>
<li>Integrate AI models into scalable backend services using Django, Flask, or FastAPI.</li>
<li>Build robust RESTful APIs and manage data pipelines for AI workflows.</li>
<li>Collaborate closely with frontend/backend engineers to bring AI features to production.</li>
</ul>
<p><b>Required Qualifications:</b></p>
<ul>
<li>Bachelor&rsquo;s/Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related fields.</li>
<li>8+ years of experience in building and deploying ML/DL models (time series, NLP, etc.).</li>
<li>Proven expertise in Computer Vision (e.g., segmentation, detection, video analysis).</li>
<li>Proficiency in Python, with frameworks like PyTorch, TensorFlow, OpenCV, and Hugging Face.</li>
<li>Solid experience in backend frameworks: Django, Flask, or FastAPI, and building APIs for AI model inference.</li>
<li>Familiarity with containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, GCP, Azure).</li>
<li>Exposure to MLOps tools and concepts (e.g., MLflow, Weights &amp; Biases, CI/CD pipelines).</li>
</ul>
<p><b>Preferred Skills:</b></p>
<ul>
<li>Knowledge of LLMs (e.g., GPT, LLaMA, Mistral), agentic AI frameworks such as LangChain, AutoGPT is a plus.</li></ul></div>

Lead Data Scientist

<div><p><b>About the role:</b></p>
<p>
The ideal candidate should have 6 to 10 years of experience working as a Business Analyst, with more than 3 years of these focused on supply chain function. This role will involve working closely with clients and internal teams to understand business needs, gather requirements for a solution, analyse processes, and supporting testing and implementation of solutions that drive success. Previous experience in the life sciences industry is a plus.</p>
<p><b>
Responsibilities:</b></p>
<div>
<ul><li>Collaborate with clients and stakeholders to gather and document business requirements.</li></ul>
<ul><li>Analyse business processes and workflows to identify areas for improvement.</li></ul>
<ul><li>Develop and maintain detailed business requirements documents, process maps, and data models.</li></ul>
<ul><li>Work with cross-functional teams, including developers, project managers, and quality assurance, to ensure solutions meet business needs.</li></ul>
<ul><li>Assist in the creation of test plans and test cases; participate in user acceptance testing (UAT).</li></ul>
<ul><li>Provide ongoing support to clients and internal teams during project implementation and post-launch.</li></ul>
<ul><li>Communicate effectively with stakeholders to ensure transparency and alignment on project goals.</li></ul>
<ul><li>Monitor project progress and provide regular updates to stakeholders.</li></ul>
</div>
<p><b>Requirements:</b></p>
<div>
<ul><li>Master&rsquo;s or bachelor&rsquo;s degree in business administration, Engineering, Information Technology, or a related field.</li></ul>
<ul><li>6 to 10 years of experience in a business analyst role, with 3 or more years of these focused on supply chain function.</li></ul>
<ul><li>Strong analytical and problem-solving skills.</li></ul>
<ul><li>Excellent communication and interpersonal skills, with the ability to translate technical concepts into business-friendly language.</li></ul>
<ul><li>Proficiency in business analysis tools and software (e.g., Microsoft Visio, Jira, Confluence).</li></ul>
<ul><li>Familiarity with Agile methodologies and experience working in an Agile environment is a plus.</li></ul>
<ul><li>Familiarity with MS PowerPoint and MS Excel.</li></ul>
<ul><li>Previous experience working in the life sciences domain is a plus.</li></ul>
</div>
<p><b>Work Location:</b></p>
<p>
The candidate will have the flexibility to work remotely with occasional travel to an office location or to a client location, when required. Ideally, the candidate will be based out of a metro city such as Delhi NCR, Bangalore.</p></div>

Lead Business Analyst Supply Chain

Join Navikenz and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Navikenz

ABOUT_COMPANY

Senior DevOps Engineer (Kubernetes & AI Infra)

Lead Data Scientist

Lead Business Analyst Supply Chain