Job Description
<p><p><b>Job Requirement</b> Senior Machine Learning Engineer.<br/><br/> <b>Location</b> Remote.<br/><br/> <b>Company Overview :</b><br/><br/> At Codvo, software and people transformations go hand-in-hand.
We are a global empathy-led technology services company.
Product innovation and mature software engineering are part of our core DNA.<br/><br/> Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.<br/><br/> We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.<br/><br/> <b>Education :</b><br/><br/>- Bachelors or Masters degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative discipline; PhDs preferred.<br/><br/>- Specialization or research in applied machine learning, MLOps, or ML systems preferred.<br/><br/> <b>Experience : </b><br/><br/>- 7+ years of experience designing, developing, and deploying ML models in production environments.<br/><br/>- 4+ years of experience in building predictive models like classification, time series modelling etc.<br/><br/>- 1+ year of experience in areas such as recommendation systems, pattern recognition, NLP.<br/><br/>- Experience with production-grade Python (preferred), as well as Java or C/C++.<br/><br/>- Hands-on experience with large-scale software architecture, APIs, and model versioning systems.<br/><br/> <b>Skills :</b><br/><br/>- Expertise in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn.<br/><br/>- Proficient in cloud-based ML platforms (e., Azure ML, Google Cloud Platform, AWS SageMaker).<br/><br/>- Solid understanding of machine learning algorithms (e., classification, regression, SVMs, ARIMA, ensemble methods, deep learning, neural network).<br/><br/>- Strong foundation in probability theory and statistical modeling (generative and discriminative).<br/><br/>- Familiarity with DevOps/MLOps practices, CI/CD pipelines, GitHub Actions, Terraform Docker, and Kubernetes.<br/><br/>- Ability to communicate technical concepts clearly to both technical and non-technical takeholders.<br/><br/>- Strong collaboration skills with cross-functional teams (engineering, analytics, product).<br/><br/>- Ability to independently manage tasks and thrive in a remote-first or hybrid environment.<br/><br/> <b>Preferred Skills :</b><br/><br/>- Experience in regulated industries (e., finance, healthcare, insurance).<br/><br/>- Excellent communication and stakeholder engagement skills.<br/><br/>- Strong understanding of deep learning architectures (e CNNs, RNNs, Transformers, GANs) Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.<br/><br/>- Proficiency in model evaluation, distributed training, and hyperparameter optimization.<br/><br/>- Proficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search).<br/><br/>- Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes).<br/><br/>- Proficient in API and Microservices technologies Track records in large-scale, real-time AI/GenAI/ML database and solution technologies Background in responsible AI/ML, model interpretability, and fairness auditing.<br/><br/> <b>Experience</b> : 7 +Years.<br/><br/></p><br/></p> (ref:hirist.tech)