We are currently looking for a highly experienced Senior Machine Learning Engineer with a strong background in ML / AI to join our growing team. This position requires a strong understanding of ML/AI concepts, practical experience with modern ML frameworks, and the ability to quickly adapt to established architectures and contribute effectively within an Agile environment. If you're excited about enhancing and extending existing systems by developing, deploying, and maintaining high-quality, production-ready machine learning models, and working with a first class global engineering team — this is for you!
Key Responsibilities:
Model Development & Enhancement: Design, develop, and implement machine learning models, with a strong focus on enhancing existing system functionalities and addressing specific project requirements.
Deep Learning & NLP: Specialize in training and optimizing Natural Language Processing (NLP) models, leveraging deep learning techniques.
LLM & GenAI Application: Apply practical experience with Large Language Models (LLMs) and other Generative AI (GenAI) technologies to solve customer problems.
ML Pipeline Development: Build and deploy robust ML pipelines using AWS services such as Bedrock and SageMaker, including managing model endpoints.
Production Support: Support deployed ML applications in production environments, ensuring their reliability, performance, and scalability.
Data Interaction: Utilize SQL proficiency to interact with and prepare data for model training and evaluation.
Collaboration & Documentation: Work closely with the team to align with current technical direction, contribute to technical documentation, and participate in code reviews and discussions.
3-5 years of professional experience as a Machine Learning Engineer or in a similar role.
Solid experience in machine learning algorithms, including linear regression, SVM, decision trees, neural networks, and clustering, along with familiarity with best practices.
Required deep learning experience, especially with training Natural Language Processing (NLP) Models.
Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Transformers, or scikit-learn.
Practical experience working with and utilizing Large Language Models (LLMs) and other Generative AI (GenAI) technologies.
Demonstrated ability to build and deploy ML models, design training pipelines, and support ML applications in production environments.
Competence in building ML Pipelines using AWS services like Bedrock and SageMaker (pipelines and model endpoints).
Proficiency in SQL.
Familiarity with scaled Agile practices and continuous improvement methodologies.
Strong problem-solving skills and attention to detail.
Excellent collaboration and communication skills.
Fluency in English.
Nice to Have:
Location: Can work from anywhere within Mexico (working from the office will be required time to time)
Offices: Av. de las Américas 1254-17th, Country Club, 44610 Guadalajara, Jal.
KMS Technology was established in 2009 as a U.S.-based software services company. With development centers in Vietnam and Mexico, we have been trusted globally for the superlative quality of our software consulting & development services, technology solutions, and engineers' expertise. We pride ourselves on creating brilliant solutions for our clients by leveraging deep expertise, advanced technologies, and delivery excellence for a shared success where everyone can reach their fullest potential. With three Business Lines:KMS Software: Leverage software domain expertise to help clients make better business decisions in technology platforms, increase speed-to-market, and gain critical development support through innovative technology solutions.KMS Solutions: Empower BFSI businesses to embrace the digital finance revolution and expedite clients’ journey towards complete digitalization, technology consulting, data analytics, software development, and software quality.KMS Healthcare: Build transformative next-gen technologies to solve healthcare’s most challenging problems, providing innovative tools and expertise to providers, payers, life sciences, and medical technology vendors.
Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
Senior Machine Learning Engineer Q&A's