Position OverviewWe are seeking a skilled Machine Learning Engineer to join our team and drive the development deployment and optimization of machine learning models and systems The ideal candidate will bridge the gap between data science research and productionready ML solutions working collaboratively to solve complex business problems through innovative ML applications across cloud and edge environmentsKey ResponsibilitiesModel Development amp Implementation Design develop and implement machine learning models and algorithms to solve business problems Optimize model performance accuracy and efficiency through feature engineering and hyperparameter tuning Research and evaluate new ML techniques frameworks and toolsProduction Systems amp Infrastructure Deploy ML models into production environments using cloud platforms and containerization technologies Build and maintain scalable ML pipelines for data processing model training and inference Implement MLOps practices including model versioning monitoring and automated retraining Ensure model reliability scalability and performance in production systems Optimize models for deployment across different environments cloud edgeEdge Deployment Deploy and optimize ML models for edge devices Implement model compression techniques quantization pruning distillation Work with edge computing frameworks and optimize for resourceconstrained environments Ensure lowlatency inference and efficient resource utilizationData Engineering amp Analysis Work with largescale datasets to extract transform and prepare data for ML applications Design efficient data pipelines Ensure data quality and implement data validation processesCollaboration amp Communication Partner with data scientists software engineers and product teams to define requirements Communicate technical findings and model performance to both technical and nontechnical stakeholders Participate in code reviews and maintain high standards for code quality Document models processes and best practicesRequired QualificationsEducation amp Experience Bachelors or Masters degree in Computer Science Machine Learning Statistics Mathematics or related field 3 years of experience in machine learning engineering or related roles Proven track record of deploying ML models in production environmentsCore Technical Skills Proficiency in Python with experience in ML libraries and frameworks Strong understanding of machine learning algorithms statistics and model evaluation techniques Experience with cloud platforms AWS and their ML services Knowledge of containerization Docker Kubernetes and orchestration tools Familiarity with ML workflow tools MLflow Kubeflow Airflow Experience with SQL and database technologies Understanding of software engineering principles and version control Git Familiarity with DevOps practices and CICD pipelinesEdge amp Mobile Deployment Skills Experience with model optimization techniques quantization pruning knowledge distillation Knowledge of edge computing frameworks TensorFlow Lite ONNX Runtime OpenVINO TensorRT Understanding of hardware acceleration GPU NPU ARM processors Experience with embedded systems and IoT device constraints Knowledge of model serving on resourceconstrained environmentsSoft Skills Strong analytical and problemsolving abilities Excellent communication and collaboration skills Ability to work in fastpaced agile environments Detailoriented with strong project management skillsAI Engineering Skills GoodtoHave Experience with large language models APIs and AI agent frameworks Understanding of prompt engineering fewshot learning and incontext learning Familiarity with RAG architectures and semantic search systems Experience building AI agents Understanding of AI safety alignment and responsible AI practices
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