machine learning engineer

Intellias

<div>
 
 
 
 Project overview
 
 
 
 
 Are you a skilled Machine Learning engineer with a passion for Computer vision, NLP or Generative AI? Do you have a knack for understanding both the technical intricacies and the business implications of data-driven solutions? If so, we have an exciting opportunity for you to join our team as machine Learning Engineer
 
 
 
 
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 Strong experience in Computer Vision, NLP, Generative AI demonstrated through relevant projects or research.
 </li>
 <li>
 Proficiency in programming languages such as Python and libraries/frameworks like TensorFlow, PyTorch, OpenCV, spaCy, etc. and cloud AI services Aws/Azure/GCP
 </li>
 <li>
 Proven ability to bridge the gap between technical concepts and business impact, with a clear understanding of how data science aligns with business goals.
 </li>
 <li>
 Excellent communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders.
 </li>
 </ul>
 
 
 
 Nice to have
 
 
 
 <ul>
 <li>
 GCP Professional Machine Learning Engineer certification (not older than a year)
 </li>
 <li>
 Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
 </li>
 </ul>
 
 
 
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Drive/Participate the ideation, development, and execution of POCs and AI related project
 </li>
 <li>
 Develop and implement machine learning models, algorithms, and data-driven solutions to address complex business problems
 </li>
 <li>
 Collaborate cross-functionally with engineering, product management, and other relevant teams to integrate data-driven functionalities into our products.
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer

Confiz

<div>We are seeking a Machine Learning Engineer with 3-7 years of experience in the field. The ideal candidate will have a strong foundation in low-level machine learning skills, data science, and advanced AI techniques. You will be working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other state-of-the-art toolchains. Additionally, familiarity with cloud operations will be beneficial. If you are passionate about pushing the boundaries of AI and enjoy working on complex challenges, we want to hear from you.
Responsibilities:
<ul><li>Design, implement, and optimize machine learning models and algorithms, focusing on low-level techniques and cutting-edge AI methodologies.</li>
<li>Develop and maintain data pipelines, perform exploratory data analysis, and apply data preprocessing techniques to ensure high-quality input for machine learning models. LLM &amp; RAG Implementation: Leverage and fine-tune Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems to create innovative solutions and enhance model performance.</li>
<li>Utilize and integrate modern toolchains and frameworks (e.g., TensorFlow, PyTorch, Hugging Face) to build and deploy machine learning models.</li>
<li>Manage and optimize machine learning workflows in cloud environments (e.g., AWS, Google Cloud, Azure), ensuring scalability and efficiency.</li>
<li>Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to align on project goals and deliver high-impact solutions.</li>
</ul>
Requirements:
<ul><li>Minimum 3 years of professional experience in machine learning and AI engineering.</li>
<li>Proficiency in Python and relevant libraries (e.g., NumPy, pandas, scikit-learn). Strong understanding of machine learning algorithms, statistical analysis, and model evaluation techniques.</li>
<li>Hands-on experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) technologies, including fine-tuning and deployment.</li>
<li>Solid background in data science principles, including data preprocessing, feature engineering, and model selection.</li>
<li>Cloud Operations: Experience with cloud platforms (AWS, Google Cloud, Azure) and knowledge of cloud-based machine learning services and deployment strategies.</li>
<li>Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face Transformers) and version control systems (e.g., Git).</li>
<li>Strong analytical and problem-solving skills, with the ability to tackle complex challenges and derive actionable insights.</li>
<li>Excellent communication skills, with the ability to present technical concepts clearly and effectively to non-technical stakeholders.</li>
<li>Experience working in an Agile or iterative development environment is a plus.</li>
</ul>
We have a global team of amazing individuals working on highly innovative enterprise projects &amp; products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast growth fintech, and multiple Silicon Valley startups. 
 
What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun. 
 
People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves. 
To know more about Confiz, visit: https://www.linkedin.com/company/confiz/</div>

Central Insurance

Location: Van Wert, OH or Dublin, OH
 We’re a team of employees who are passionate about delivering best-in-class customer service and innovation in the industry. We prioritize integrity, relationships, and excellence in all aspects of our work.
 
Our employees can fully utilize their talents and bring their best selves to work. We believe who you are is just as important as what you do!
 
The data science center of excellence team at Central is looking for a passionate machine learning engineer to work on AI/ML solutions in support of our business stakeholders at Central. As a Machine Learning Engineer, you will be responsible for deploying models in the cloud as well as on-premises, shared Python frameworks, and data pipelines that integrate AI/ML models with Central’s system and customer-facing applications. Focusing on AI/ML model training and inference pipelines, you will use your technical skills, as well as your domain expertise, to develop innovative solutions. If you have a desire to deliver business value through technology designs in an environment that will allow you to grow and innovate, we will be delighted to have you.
 How You’ll Make an Impact
 <ul>
<li>Develop machine learning workflows and end-to-end pipelines for data preparation, training, deployment, monitoring and ensure that the quality of architecture and designs of machine learning systems based on established policies</li>
<li>Conducts statistical analysis, including predictive and prescriptive modeling</li>
<li>Build effective monitoring to monitor the health of your system, and jump in to handle outages of models in production</li>
<li>Collaborate closely with product teams to lead and own API development, maintaining machine learning infrastructure, and seamlessly integrating machine learning features into products</li>
<li>Consult with data engineers in the development of data pipelines, packages, and tools that the data science team utilizes as a key stakeholder</li>
<li>Technical and programmatic support through the entire project life cycle including concept development, system definition, acquisition planning, source selection, system design, development, integration and test, system delivery, and deployment</li>
<li>Build production-grade solutions to scale, manage, and serve machine learning models and data science solutions</li>
<li>Write and edit documentation and technical requirements, including evaluation plans, confluence pages, white papers, presentations, test results, technical manual, formal recommendations and reports</li>
</ul>
What You’ll Bring
 <ul>
<li>Master’s degree in computer science, engineering, applied statistics or related field</li>
<li>Or Bachelor’s degree in computer science, engineering, applied statistics or related field and 2 years experience in machine learning</li>
<li>Or 4 years experience in machine learning</li>
<li>Excellent communication skills including written, verbal, and technology diagrams</li>
<li>Understanding of the model development lifecycle and has had exposure to DevOps/MLOps/LLMOps/ModelOps</li>
<li>Experience with enterprise Cloud ML Services (i.e., Sagemaker, AzureML, Vertex AI), and open source AI/ML frameworks</li>
<li>Strong analytical and problem-solving skills</li>
<li>Ability to work both independently and in a team environment</li>
<li>Strong organizational, planning & problem-solving skills</li>
<li>Ability to understand Central Insurance’s policies and processes</li>
</ul>
Preferred
 <ul>
<li>Azure certification or AWS certification</li>
<li>Exposure in continuous integration & delivery (CI/CD) practices and tools (Git, Jenkins, uDeploy)</li>
<li>Exposure in with building container-based systems such as Docker</li>
<li>Exposure in relational and dimensional data modeling techniques</li>
<li>Exposure in machine learning models and concepts: regression, random forest, boosting, NLP, and deep learning</li>
<li>Exposure in developing and deploying complex and scalable software systems in the analytics space</li>
<li>Exposure in Azure Data Lake or other cloud data warehousing solutions</li>
<li>Exposure in triaging, troubleshooting, and fixing issues in Production environments</li>
<li>Exposure with orchestration and scheduling tools (Control-M)</li>
</ul>
Work Authorization
 Central will only employ those who are legally authorized to work in the United States. This is not a position for which sponsorship will be provided. Individuals with temporary visas such as E, F-1(including those with OPT or CPT) , H-1, H-2, L-1, B, J or TN, or who need sponsorship for work authorization now or in the future, are not eligible for hire.
 Equal Opportunity Employer
 It is the policy of Central that all recruiting, hiring, training, compensation, overtime, job classification and assignment, facilities, promotions, transfers, employee treatment and all other terms and conditions of employment shall be maintained in a manner which will not discriminate against any person because of race, color, age, sex, national origin, ancestry, religion, marital status, military status, or disability. The applicant should respond to questions on this application in a way that will not divulge such information.

BayOne Solutions

Job Role Summary: 
Position: Machine Learning Engineer
 
Location: Remote (India).
 
Type: Full-time (with BayOne).
 
Work Time : IST (02.00 PM to 10.00 PM IST).
 
Key Skills & Experience: 
Proficiency with ML frameworks (TensorFlow, PyTorch)
 
NLP and Large Language Models (LLMs) experience
 
Strong understanding of generative models and applications
 
Programming skills in Python, Go, or Java
 
API development and model integration expertise
 
Familiarity with Docker, Kubernetes Knowledge of CI/CD pipelines, databases, data lakes, or real-time data processing tools

Grace Multitrading Company

MI Teams &ndash; Sr. AI EngineerEducation:<ul><li>BE / BTech or ME in Information Technology / Computer Science Engineering.</li><li>Certifications in Machine Learning / Artificial Intelligence preferred.</li></ul>Experience &amp; Skills Required (3&ndash;5 Years):<ul><li>Proven expertise in AI/ML model development and deployment (Regression, Classification, Neural Networks).</li><li>Hands-on experience with Deep Learning (DL), Natural Language Processing (NLP), and LLMs (GPT, LLaMA, HuggingFace models, etc.).</li><li>End-to-end experience in AI/ML projects: data preprocessing, model training, testing, and cloud deployment.</li><li>Strong programming in Python, Java, C, C++.</li><li>Familiarity with DevOps/Agile methodologies, Azure DevOps, Jira, Git.</li><li>Cloud experience with AWS, Azure, or GCP (SageMaker, Vertex AI Studio, Azure AI/ML services).</li><li>Knowledge of API development, integration &amp; security.</li><li>Strong communication and prior client-facing project leadership.</li></ul>Additional Capability Requirements within AI Teams (Preferred):<ul><li>Software Engineering (C, C++, GitHub &ndash; mandatory).</li><li>UI &amp; Frontend Development (modern frameworks).</li><li>Backend Engineering with DevSecOps.</li><li>DBMS and Data Encryption expertise.</li><li>System Architecture design &amp; deployment.</li><li>Experience with Docker &amp; Kubernetes.</li><li>Linux Administration.</li><li>Networking &ndash; CCNA certified.</li><li>AI/ML Specialists &ndash; Python, TensorFlow, R.</li><li>Vision Systems &ndash; image/video data handling, compression &amp; decompression.</li></ul>Job Types: Full-time, PermanentPay: Up to &#8377;1,000,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Provident Fund</li></ul>Work Location: In person

Arc Inventor

Arc Inventador is a fast-growing technology company focused on building scalable and innovative SaaS (Software as a Service) solutions for global clients. We specialize in software development, cloud-based product engineering, and end-to-end digital transformation. Our team is passionate about delivering high-performance platforms that solve real-world business challenges across multiple industries.The ML Engineer will be responsible for designing, developing, and deploying machine learning solutions focused on Natural Language Processing (NLP), conversational AI, and speech technologies. You will drive innovation in automation and intelligent workflows, collaborating closely with backend engineers, product teams, and voice platform specialists. This role demands both deep technical expertise in ML/NLP and a practical, product-centric mindset.Key Responsibilities<ul><li>Develop and deploy NLP pipelines for intent detection, entity extraction, sentiment analysis, and conversational flow management using NLTK, spaCy, or similar libraries.</li><li>Design and implement machine learning models to automate dialog management, FAQ handling, and multi-turn conversation flows for voice and chat channels.</li><li>Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) technologies (e.g., Whisper, Google STT/TTS, Amazon Polly).</li><li>Fine-tune and maintain language models for industry-specific conversational experiences.</li><li>Collaborate with software engineers and product owners to build scalable, production-ready ML APIs and microservices.</li><li>Analyze large, multilingual datasets and annotate data to train, validate, and optimize ML models.</li><li>Monitor and optimize model performance, latency, and reliability in production.</li><li>Prototype and implement intelligent automation features (e.g., call summarization, intent routing, IVR automation).</li><li>Document research findings, pipelines, and contribute to knowledge sharing within the team.</li><li>Stay abreast of the latest advancements in conversational AI, NLP, and speech processing.</li></ul>Required Skills &amp; Experience<ul><li>3&ndash;4 years of professional experience in ML Engineering or NLP-focused Data Science roles.</li><li>Proven hands-on experience with NLTK (and/or spaCy, Transformers) for NLP pipeline development.</li><li>Strong Python programming skills: familiarity with libraries such as scikit-learn, PyTorch, or TensorFlow.</li><li>Experience developing, deploying, and maintaining STT/TTS solutions for production (Whisper, Google STT/TTS, Amazon Polly, or similar).</li><li>Solid understanding of conversational AI, dialog management, and automation for contact center or voice platforms.</li><li>Experience working with REST APIs, microservices, and deploying ML models as web services.</li><li>Exposure to handling, processing, and annotating large-scale text/audio datasets.</li><li>Familiarity with Agile development, version control (Git), and collaborative workflows.</li></ul>Job Type: Full-timeWork Location: In person

ServiceNow

<div>Company Description 
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today &mdash; ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500&reg;. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. 
Job Description 
Team Overview:
Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.
What you get to do in this role:<ul><li>
Design, develop, and evaluate end-to-end machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.</li><li>
Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.</li><li>
Conduct cutting-edge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.</li><li>
Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.</li><li>
Fine-tune and deploy large-scale models, incorporating prompt engineering, few-shot learning, and retrieval-augmented techniques.</li><li>
Collaborate cross-functionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to open-source or peer-reviewed ML/AI research.</li><li>
Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.</li><li>
Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.</li><li>
Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.</li></ul> 

Qualifications 
Key qualifications:<ul><li>
Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have</li><li>
Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization</li><li>
2+ years of experience in machine learning, deep learning, LLM, with a track record of applied research or experimentation.</li><li>
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.</li><li>
Hands-on experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.</li><li>
Proven experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.</li><li>
Familiarity with data-centric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.</li><li>
Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.</li><li>
Practical experience deploying models using inference platforms like Triton, ONNX in production environments.</li><li>
Experience working with MLOps stacks: CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.</li><li>
Excellent communication skills with the ability to explain complex ML ideas to non-technical stakeholders and contribute to scientific documentation.</li></ul> 
Additional Information 
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. &copy;2025 Fortune Media IP Limited. All rights reserved. Used under license.</div>

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