ml model developer

Amogha Group

Required Qualifications:&middot; Master&rsquo;s or PhD in Computer Science, Data Science, Statistics, or related field.&middot; 5&ndash;8 years of experience in data science and ML, with strong enterprise project delivery experience.&middot; Proven success in building and deploying ML models and recommendation systems at scale.&middot; 2+ projects delivered involving LLMs and Generative AI, with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, Lang Chain, Vector DBs, or model fine-tuning.&middot; Advanced Python programming skills and experience with ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, and Tensor Flow).&middot; Experience with cloud-based ML/AI platforms (e.g., Vertex AI, AWS SageMaker, and Azure ML).&middot; Strong understanding of system architecture, APIs, data pipelines, and model integration patterns.Preferred Qualifications:&middot; Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, and CrewAI).&middot; Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents.&middot; Working knowledge of MLOps best practices including model versioning, CI/CD for ML, and model monitoring.&middot; Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams.Job Type: Full-timeWork Location: In person

Data Scientists – ML, GenAI & Agentic AI

Code Graphers

Key ResponsibilitiesModel Development &amp; Implementation<ul><li>Design, train, and fine-tune machine learning and deep learning models for NLP, computer vision, and predictive analytics tasks.</li><li>Work with frameworks like TensorFlow, PyTorch, and Scikit-learn for building and deploying ML models.</li><li>Assist in developing RAG (Retrieval Augmented Generation) pipelines and LLM-based applications under senior supervision.</li><li>Implement and maintain APIs using frameworks like FastAPI, Flask, or Django for ML model integration.</li></ul>Data Handling &amp; Preprocessing<ul><li>Perform data cleaning, feature extraction, and transformation for model readiness.</li><li>Contribute to building and maintaining data pipelines for training and inference stages.</li></ul>Deployment &amp; MLOps<ul><li>Containerize ML solutions using Docker and participate in deploying models to production environments.</li><li>Support MLOps workflows, version control using DVC, and CI/CD pipelines for continuous delivery.</li></ul>Research &amp; Collaboration<ul><li>Stay updated with the latest trends in AI, LLMs, and computer vision.</li><li>Collaborate with cross-functional teams, data engineers, and senior ML engineers to ensure robust system integration.</li><li>Document workflows, experiments, and technical findings clearly.</li></ul>QualificationsEducation:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.</li></ul>Experience:<ul><li>2&ndash;3 years of hands-on experience in machine learning model development and deployment.</li><li>Strong understanding of fundamental ML algorithms and their mathematical background.</li><li>Exposure to NLP, Computer Vision, or LLM-based systems is preferred.</li></ul>Technical Skills:<ul><li>Proficient in Python and familiar with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.</li><li>Knowledge of LLMs, LangChain, or RAG frameworks is a plus.</li><li>Experience with RESTful APIs and backend integration.</li><li>Familiarity with Git, Docker, and cloud platforms (AWS, GCP, or Azure).</li></ul>Nice to Have<ul><li>Experience with LoRA, QLoRA, or model fine-tuning techniques.</li><li>Familiarity with image classification, object detection, or segmentation tasks.</li><li>Exposure to auto-scaling, model optimization, or embedded ML applications.</li><li>Interest in learning advanced AI concepts like multi-agent systems, meta-learning, and generative AI.</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>Did you have experience with Computer vision, LLM, nlp and Audio?</li></ul>Experience:<ul><li>Machine Learning : 2 years (Required)</li></ul>Work Location: In person

Machine Learning Engineer

Devsinc

<div>
 Application &amp; Model Development:
 
 
 Design, develop, and deploy Python-based applications and AI/ML models.
 
 
 Data Handling:
 
 
 Collect, clean, and preprocess structured and unstructured data for model training.
 
 
 Model Training &amp; Evaluation:
 
 
 Implement machine learning and deep learning algorithms; evaluate performance using appropriate metrics.
 
 
 API Integration:
 
 
 Create and integrate APIs for serving ML models into applications or web services.
 
 
 Research &amp; Innovation:
 
 
 Stay updated with AI/ML trends, frameworks (TensorFlow, PyTorch, Scikit-learn), and improve model efficiency.
 
 
 Automation &amp; Scripting:
 
 
 Develop automation scripts and data pipelines to support AI workflows.
 
 
 Collaboration:
 
 
 Work with data engineers, developers, and product teams for end-to-end solution delivery.
 
 
 Version Control &amp; Documentation:
 
 
 Maintain clean code, version control (Git), and project documentation.
 
 
 Testing &amp; Deployment:
 
 
 Test models, deploy to production, and monitor performance using cloud or on-prem setups.
 
 
 Continuous Learning:
 
 
 Explore emerging AI/ML technologies and contribute to innovation projects.
 
 
 
 Requirements
 
 
 
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related field.
 
 
 Develop Python-based AI/ML apps &amp; models
 
 
 Preprocess &amp; analyze data
 
 
 Train, test, and evaluate models
 
 
 Build &amp; integrate APIs for ML services
 
 
 Use TensorFlow, PyTorch, Scikit-learn
 
 
 Create automation scripts &amp; data pipelines
 
 
 Collaborate across teams for deployment
 
 
 Maintain code, versioning, and documentation
 
 
 Deploy &amp; monitor ML solutions
 
 
 Keep learning new AI/ML tools &amp; methods
</div>

Associate Software Engineer -Python/AI/ML

NAFFCO FZCO

Job Purpose:To design, build, and integrate AI modules into IoT/IIoT and digital platforms by managing the full machine learning lifecycle — from model training to deployment — ensuring scalable and business-aligned solutions. <h3>Key Responsibilities:</h3>· AI Module Development & Integration – Design and build AI modules that integrate seamlessly into IoT/IIoT and digital platforms.· Machine Learning Model Lifecycle – Develop, train, validate, and maintain ML models for predictive maintenance, anomaly detection, optimization, and risk scoring.· System & Platform Integration – Work with APIs, data pipelines, and dashboards to integrate AI solutions into enterprise and industrial systems.· Model Training– Prepare data, select algorithms, and train models with high accuracy and scalability.· Production Deployment – Deploy, monitor, and optimize ML models in production environments (cloud and edge).· Collaborate with cross-functional product and engineering teams to ensure AI solutions meet business requirements. <h3>Qualifications & Skills:</h3>· Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.· Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn).· Proven hands-on experience in ML model training and production deployment.· Solid understanding of IoT/IIoT platforms (AWS IoT, Azure IoT, or custom).· Experience in data engineering & API integration.· Familiarity with cloud platforms (AWS, Azure, GCP) and containerization(Docker, Kubernetes).<h3>Key Competencies:</h3>· End-to-end ownership of ML model lifecycle.· Strong analytical and problem-solving skills.· Ability to bridge technical solutions with business impact.

AI Module Development Engineer – IoT & Digital Platforms

Antons

Key Responsibilities 
<ul>
<li>
 ML Pipeline Engineering: Design, build, and maintain scalable ML pipelines leveraging MLFlow, Databricks, and Azure ML.
</li>
<li>
 Model Development: Develop and optimize ML models, particularly for healthcare predictive analytics.
</li>
<li>
 Integration: Embed ML models into KPI-driven data processing and analytics workflows.
</li>
<li>
 Model Lifecycle Management: Implement model monitoring, drift detection, retraining, and continuous improvement strategies.
</li>
<li>
 Collaboration: Work closely with data engineers, data scientists, and business stakeholders to deploy solutions that deliver measurable impact.
</li>
</ul>

Senior Data Science Engineer

The University of Southern MIssissippi

<div>Artificial Intelligence/Machine Learning (AI/ML) Engineer

The University of Southern Mississippi is currently accepting applications for the position of Artificial Intelligence/Machine Learning (AI/ML) Engineer. 
<div><div><div><div>Position Details</div>
</div> 
<div><div>Location</div> <div>Marine Research Center 
 
1030 West Pier, Port of Gulfport 
Gulfport, Mississippi, 39501 
United States
</div></div> 
<div><div>Division</div> <div>Ocean Enterprise</div>
</div> 
<div><div>Position Type</div> <div>Staff</div>
</div> 
<div><div>Employment Status</div> <div>Full Time</div>
</div> 
<div><div>Grant Funded</div> <div>Yes</div>
</div> 
<div><div>Salary Range</div> <div>85,349.00 - 115,000.00</div>
</div> 
<div><div>Pay Grade</div>
E16 
</div> 
<div><div>Posting Close Date</div> <div>February 1, 2026</div>
</div> 
</div></div>Special Instructions to Applicants 
Applicants must be currently authorized to work in the United States on a full-time basis without the need for visa sponsorship. The University will not sponsor applicants for work visas (e.g., H-1B). 
 
Job Summary 
This is an early to mid-career role that will require the incumbent to design, build and maintain machine learning (ML) models focusing on making AI models practical and scalable for real-world applications, often bridging the gap between data science and software engineering. The position is located at the USM Roger F. Wicker Center for Ocean Enterprise. 
 
Primary Duties and Responsibilities 
<ul><li>
Design, develop, and optimize machine learning models for diverse business and research applications.</li><li>
Collaborate with data scientists, software engineers, and product teams to integrate ML models into production systems and ensure scalability.</li><li>
Lead data preparation efforts, including preprocessing, feature engineering, and exploratory data analysis to support model development.</li><li>
Evaluate and refine models using appropriate metrics, improving accuracy, efficiency, and robustness against real-world data challenges.</li><li>
Maintain and enhance ML pipelines and infrastructure, ensuring reliability, reproducibility, and continuous improvement.</li><li>
Stay current with AI/ML research and apply emerging methods to solve complex practical problems.</li><li>
Translate research into practice by collaborating with principal investigators and research teams, and assisting in preparing technical reports, visualizations, and academic publications.</li><li>
Document models, processes, and codebases to ensure transparency, reproducibility, and effective knowledge sharing across teams.</li></ul>
<div>
Minimum Qualifications 
Bachelor's degree from an accredited college or university in Computer Science, Data Science, Engineering or a related field and 6 years of experience or a Master&rsquo;s Degree from an accredited college or university in Computer Science, Data Science, Engineering or a related field and 4 years of experience. Demonstrated experience working in the full lifecycle of an ML Model. U.S. Citizenship with the ability to obtain a Government clearance. A valid driver&rsquo;s license and eligibility to receive a Trusted Worker Identification Card (TWIC) 
 
Knowledge, Skills &amp; Abilities</div><ul><li>
Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, and XGBoost.</li><li>
Experience with data manipulation tools like Pandas, NumPy, and SQL.</li><li>
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud (especially services like SageMaker, Vertex AI, etc.).</li><li>
Experience with model deployment tools and frameworks (e.g., Docker, FastAPI, Flask, MLflow).</li><li>
Strong understanding of supervised and unsupervised learning, neural networks, NLP, and computer vision.</li><li>
Experience with version control systems (e.g., Git) and CI/CD pipelines.</li><li>
Excellent problem-solving skills and ability to work independently and in teams.</li></ul><div></div><div>
Preferred Qualifications 
Experience with MLOps practices and tools. 
Familiarity with big data technologies (e.g., Spark, Hadoop). 
Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Plotly). 
Contributions to open-source projects or published research in AI/ML 
Proficiency in programming languages like C, Java, C++ and Python</div>
<div></div>
About The University of Southern Mississippi
 
Since our founding in 1910, The University of Southern Mississippi has remained dedicated to preparing students for success. We deliver programs to more than 13,000 students in Hattiesburg and Long Beach, at teaching and research sites across the Mississippi Gulf Coast, as well as online. We are a community-engaged Carnegie R1 university, earning distinction as one of the nation's leading research institutions. 
 
Southern Miss is known for pioneering work in polymer science, ocean science, spectator sports safety and security, and bringing language to children with communication disorders. We are also a national leader in a broad range of disciplines, including cybersecurity, hydrography, nutrition, aquaculture, kinesiology, and economic development, among others.
 
 
We produce graduates ready to enter fields that are leading the way in emerging technologies through programs such as computer engineering, information technology, and ocean engineering. We&rsquo;re developing the next generation of business leaders, while also responding to critical workforce shortages by producing skilled professionals in education and nursing. With a tradition of excellence in the arts, we are one of only 36 public institutions in the nation accredited in four major areas of the arts. Home to the Golden Eagles, our student-athletes compete in 17 NCAA Division I sports. With a culture marked by passion and persistence, Southern Miss is delivering graduates who are ready for life. For more information, visit www.usm.edu.

The University of Southern Mississippi is an equal opportunity employer, and all qualified applicants will receive consideration for employment. EOE/VETS/DISABILITY.</div>

Artificial Intelligence/Machine Learning (AI/ML) Engineer

eClerx

<div>Roles and Responsibilities
<ul><li>Industrial experience of developing Gen AI / ML models and experience in Agentic AI development
</li><li>Experience of software development in python programming language
</li><li>Working knowledge of standard software engineering practices like version control, debugging, code coverage etc
</li><li>Research and develop statistical learning models for data analysis
</li><li>Collaborate with product management and engineering departments
</li><li>Understand life-cycle of model development from initiation till production deployment
</li><li>Processing, cleansing, and validating the integrity of data to be used for analysis
</li><li>Analyzing large amounts of information to find patterns and solutions
</li><li>Presenting results in a clear manner
</li><li>Propose solutions and strategies to tackle business challenges
</li></ul>Skills &amp; Qualifications
<ul><li>B.E/ B. Tech in computer science or MCA or equivalent
</li><li>Good understanding of data structure and algorithms
</li><li>Proven Experience as Data Scientist.
</li><li>4+ years of experience in data science
</li><li>Excellent programming skills in Python (mandatory)
</li><li>Good practical exposure of writing database query languages like SQL
</li><li>Good applied statistical skills
</li><li>Advanced pattern recognition and predictive modeling experience.
</li><li>Working experience of either text/image/video analytics
</li><li>Excellent Communication Skills.</li></ul></div>

Process Manager

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