
Cloud Native MLOps Specialist
1 day ago
We are seeking a talented individual to lead our AI and Machine Learning efforts. As a seasoned Data Science and Engineering professional, you will be responsible for designing, developing, and deploying scalable machine learning solutions leveraging modern technologies and methodologies.
Main Responsibilities- End-to-End ML Lifecycle Management:
- Generative AI Enablement:
- MLOps Pipelines:
- Model Performance Optimization:
- Collaboration:
- Monitoring and Maintenance:
- Data Engineering:
- Documentation:
- Research and Innovation:
- Bachelor's or higher degree in Computer Science, Mathematics, Engineering, or a related field with strong analytical and computational skills.
- At least 5 years of hands-on experience designing, building, and deploying ML applications in large-scale data environments.
- Technical Proficiency:
- Expertise in ML frameworks like TensorFlow, PyTorch, and HuggingFace, alongside GenAI technologies such as LLMs, GANs, and Transformer Architectures.
- Experience with flash attention, VectorDB, CUDA, and GraphDBs (e.g., Neo4j).
- Experience in building multi-agent systems using LangFlow.
- Skilled in capacity planning and designing scalable, efficient infrastructure.
- Strong programming skills in Python; additional languages are a plus.
- Proficiency with Big Data tools such as Hadoop, Spark, Kafka, and Elasticsearch.
- Experience with relational and NoSQL systems like HBase, MongoDB, and PostgreSQL.
- Knowledge of open data lakehouse architectures, including object storage solutions like MinIO, S3, and Iceberg.
- Deep understanding of model evaluation techniques and metrics.
- Hands-on experience with Kubeflow, Airflow, or equivalent for pipeline orchestration.
- Proficiency in AIOps, LLMOps, and MLOps(MLFlow) for streamlined AI/ML lifecycle management.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Experience in working with cloud platforms (Azure and GCP) and hybrid infrastructure.
- Proficiency in Linux systems and bash scripting.
- Experience with deep learning, and NLP techniques are plus.
- Experience with Big Data technologies such as Hadoop, Spark, Solr/Elastic Search, Nifi is a plus.
- Solid understanding of data pipelines, data wrangling, and feature engineering for ML models.
- Strong problem-solving abilities, attention to detail, and a collaborative mindset.
- Experience working in agile teams and delivering results in fast-paced environments.
- Knowledge of privacy, cybersecurity and model interpretability for AI governance.
We offer a range of benefits, including Vflexy: Flexible Benefits Program, Hybrid working kit, Ergonomic kit allowance, Employee assistance hotline & counselling, Comprehensive and flexible private health insurance, and Discounted price deals for wide range of products & services.
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