ml engineer

Zyoin Group

<div>
 <p>
  Location:
  <strong>
   Bangalore
  </strong>
 </p>
 <p>
  Position
  <strong>
   :
  </strong>
  Senior ML-Engineer
 </p>
 <p>
  Experience:
  <strong>
   6-9 years
  </strong>
 </p>
 <p>
  Workplace type:
  <strong>
   Work From Office
  </strong>
 </p>
 <p>
  <strong>
   Notice Period- Immediate -30 days
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Description
  </strong>
 </p>
 <p>
  5-7 years of experience in machine learning engineering, with a significant track record in the
 </p>
 <p>
  developing production grade models and model pipelines in a regulated industry such as healthcare.
 </p>
 <p>
  ● Hands-on expertise in working with large language models (e.g., GPT, BERT), computer vision
 </p>
 <p>
  models, and classic NLP technologies.
 </p>
 <p>
  ● Proficient in programming languages such as Python, with extensive experience in ML
 </p>
 <p>
  libraries/frameworks like TensorFlow, PyTorch, OpenCV, etc.
 </p>
 <p>
  ● Strong understanding of deep learning techniques, model fine-tuning, hyper parameter
 </p>
 <p>
  optimization, and model optimization
 </p>
 <p>
  ● Proven experience in deploying and managing ML models in production environments.
 </p>
 <p>
  ● Excellent analytical skills, with a problem-solving mindset and the ability to think strategically.
 </p>
 <p>
  ● Strong communication skills for articulating complex concepts to diverse audiences.
 </p>
 <p>
  ● Working knowledge or experience in MLOps and LLMOps using tools like mlflow, kubeflow
 </p>
 <p>
  ● Working knowledge of basic software engineering principles and best practices
 </p>
 <p>
  ● Demonstrated working knowledge and experience on classic ML techniques and frameworks.
 </p>
 <p>
  ● Nice to have : Knowledge of Cloud vendor based ML Platforms such as Azure ML, Sagemaker
 </p>
</div>


Senior ML Engineer

Nets-international Communication

<p>NETS International Group is seeking a <b>highly skilled AI/ML Engineer</b> to join our innovation and analytics division. The ideal candidate will have strong expertise in <b>machine learning, data science, and AI model deployment</b>, with the ability to design, train, and optimize predictive systems that deliver measurable impact.</p><p>This role involves working closely with <b>data engineers, software developers, and cloud architects</b> to integrate AI-driven solutions into scalable enterprise applications using modern frameworks, cloud services, and MLOps practices.</p><p><b>Key Responsibilities:</b></p><ul><li>Design, develop, and deploy <b>machine learning models</b> and <b>AI-based solutions</b> for predictive analytics, automation, and decision support.</li><li>Perform <b>data preprocessing, feature engineering, and model evaluation</b> using statistical and deep learning techniques.</li><li>Implement models using <b>Python frameworks</b> such as <b>TensorFlow, PyTorch, Scikit-learn, and Keras</b>.</li><li>Collaborate with data engineers to build and maintain <b>data pipelines</b> for training and inference.</li><li>Integrate AI models into <b>production environments</b> using APIs, containers, and cloud-based services (AWS Sagemaker, Azure ML, or Google AI Platform).</li><li>Work with large datasets from diverse sources &mdash; structured, unstructured, and streaming &mdash; ensuring <b>data quality and security</b>.</li><li>Develop and optimize <b>MLOps pipelines</b> for continuous training, deployment, and monitoring of machine learning models.</li><li>Conduct <b>research and experimentation</b> to evaluate new AI techniques and frameworks that can enhance enterprise systems.</li><li>Collaborate cross-functionally with business and technical teams to translate requirements into actionable AI/ML solutions.</li><li>Ensure <b>model explainability, fairness, and compliance</b> with company and industry standards.</li></ul><p><b>Qualifications:</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in <b>Computer Science, Data Science, Artificial Intelligence, or related field</b>.</li><li>Proven experience (3+ years) in <b>machine learning, AI model development, and data analytics</b>.</li><li>Proficiency in <b>Python</b>, with strong knowledge of libraries such as <b>NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch</b>, and <b>Keras</b>.</li><li>Strong understanding of <b>data preprocessing, model selection, feature engineering, and evaluation metrics</b>.</li><li>Experience with <b>SQL and NoSQL databases</b> (MySQL, MongoDB, PostgreSQL, etc.).</li><li>Hands-on experience with <b>cloud-based AI/ML services</b> (AWS Sagemaker, Azure ML, GCP AI Platform).</li><li>Familiarity with <b>DevOps/MLOps tools</b> (Docker, Kubernetes, MLflow, or Kubeflow) for scalable deployment.</li><li>Good grasp of <b>statistics, probability, linear algebra, and data visualization tools</b> (Matplotlib, Seaborn, Power BI).</li><li>Knowledge of <b>Natural Language Processing (NLP), Computer Vision</b>, or <b>Generative AI</b> is a strong plus.</li><li>Excellent problem-solving, analytical, and collaboration skills.</li></ul><p>Job Type: Full-time</p><p>Ability to commute/relocate:</p><ul><li>Muscat: Reliably commute or planning to relocate before starting work (Required)</li></ul><p>Application Question(s):</p><ul><li>what is your monthly current salary with currency?</li><li>what is your monthly expected salary with currency?</li><li>what is your notice period?</li></ul><p>Education:</p><ul><li>Bachelor's (Required)</li></ul><p>Experience:</p><ul><li>AI ML: 4 years (Required)</li></ul>

AI ML Engineer

Hewlett Packard Enterprise | HPE

<div>AI/ML Engineer<p><br>
</p>This role has been designed as &lsquo;Hybrid&rsquo; with an expectation that you will work on average 2 days per week from an HPE office.<p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>
Who We Are:</b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p>
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today&rsquo;s complex world. Our culture thrives on finding new and better ways to accelerate what&rsquo;s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><p><b>
Job Description:</b></p><p><br>
</p><p><b>HPE Operations </b>is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers&rsquo; outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today&rsquo;s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what&rsquo;s next for you.</p><p></p><p><b>
What you'll do:</b></p><p></p><p>
We are seeking an experienced <b>AI / ML Engineer</b> with 4+ years of expertise in designing, developing, and deploying <b>machine learning and artificial intelligence solutions</b> at enterprise scale. The ideal candidate will build scalable ML pipelines, apply deep learning and advanced analytics, and collaborate with data scientists and engineers to transform business problems into intelligent, data-driven solutions.</p><p></p><p><b>
Key Responsibilities</b></p><ul><li><b>
Model Development &amp; Deployment</b><ul><li>
Design, train, and optimize <b>ML/DL models</b> for classification, prediction, NLP, computer vision, and recommendation systems.</li><li>
Deploy ML models into production using <b>MLOps frameworks</b> (Kubeflow, MLflow, SageMaker, Vertex AI, Azure ML).</li><li>
Develop reusable ML components for scalability and automation.</li></ul></li><li><b>
Data Engineering for ML</b><ul><li>
Work with large-scale datasets for feature extraction, cleaning, and transformation.</li><li>
Implement <b>data pipelines</b> for real-time and batch ML workloads.</li><li>
Ensure data quality, consistency, and lineage across pipelines.</li></ul></li><li><b>
MLOps &amp; Automation</b><ul><li>
Build end-to-end automated <b>ML lifecycle pipelines</b> (training, testing, deployment, monitoring).</li><li>
Integrate CI/CD practices into ML model deployment.</li><li>
Implement drift detection, continuous learning, and retraining strategies.</li></ul></li><li><b>
Performance &amp; Optimization</b><ul><li>
Optimize algorithms for speed, accuracy, and cost efficiency.</li><li>
Leverage GPU/TPU environments for high-performance training.</li><li>
Benchmark models and fine-tune hyperparameters for business KPIs.</li></ul></li><li><b>
Security &amp; Governance</b><ul><li>
Ensure compliance with ethical AI practices and regulatory frameworks.</li><li>
Implement security measures for ML models (adversarial robustness, secure APIs).</li><li>
Collaborate with cybersecurity and governance teams for responsible AI adoption.</li></ul></li><li><b>
Collaboration &amp; Innovation</b><ul><li>
Work with <b>data scientists, data engineers, and business analysts</b> to align AI solutions with business outcomes.</li><li>
Mentor junior engineers and contribute to best-practice frameworks.</li><li>
Stay updated on <b>emerging AI/ML research, tools, and technologies</b>.</li></ul></li></ul><p></p><p><b>
What you need to bring:</b></p><p><b>
Required Skills &amp; Experience</b></p><ul><li>
4+ years in <b>AI/ML engineering, data science, or applied machine learning</b>.</li><li>
Proficiency in <b>Python, R, or Scala</b> with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost).</li><li>
Strong background in <b>statistics, data mining, and algorithm design</b>.</li><li>
Hands-on experience with <b>cloud AI/ML platforms</b> (AWS SageMaker, Azure ML, GCP Vertex AI).</li><li>
Familiarity with <b>MLOps tools</b> (Kubeflow, MLflow, Airflow, Docker, Kubernetes).</li><li>
Strong knowledge of <b>SQL/NoSQL databases and data lakes</b>.</li></ul><p></p><p><b>
Preferred Knowledge</b></p><ul><li>
Experience with <b>Generative AI (LLMs, diffusion models, transformers)</b>.</li><li>
Domain knowledge in <b>NLP, CV, or reinforcement learning</b>.</li><li>
Exposure to <b>streaming data ML</b> (Kafka, Flink, Spark Streaming).</li><li>
Familiarity with <b>responsible AI frameworks</b> (Fairness, Explainability, Bias detection).</li></ul><p></p><p><b>
Education &amp; Certifications</b></p><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, AI/ML, or related field.</li><li>
Preferred certifications:<ul><li>
AWS Certified Machine Learning &ndash; Specialty / Azure AI Engineer Associate / GCP ML Engineer.</li><li>
TensorFlow or PyTorch professional certifications.</li></ul></li></ul><p></p><div><div><div><div><div><div><div><p><b>
Additional Skills:</b></p></div></div></div></div></div></div></div>
Accountability, Accountability, Active Learning, Active Listening, Bias, Business Growth, Client Expectations Management, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Customer Centric Solutions, Customer Relationship Management (CRM), Design Thinking, Empathy, Follow-Through, Growth Mindset, Information Technology (IT) Infrastructure, Infrastructure as a Service (IaaS), Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity, Process Improvements, Product Services, Relationship Building {+ 5 more}<p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>
What We Can Offer You:</b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p><b>
Health &amp; Wellbeing</b></p><p>
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.</p><p></p><p><b>
Personal &amp; Professional Development</b></p><p>
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have &mdash; whether you want to become a knowledge expert in your field or apply your skills to another division.</p><p></p><p><b>
Unconditional Inclusion</b></p><p>
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.</p><p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>
Let's Stay Connected:</b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p>
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p>#india
#operations<p></p><p><b>
Job:</b></p>
Services<p><b>
Job Level:</b></p>
TCP_02<p><br>
</p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p>HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p><b>
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.</b></p><p><br>
</p><p>HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.</p><p><br>
</p><p><b>No Fees Notice &amp; Recruitment Fraud Disclaimer</b></p><p></p><p><i><br>
It has come to HPE&rsquo;s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates. These scammers often seek to obtain personal information or money from candidates.</i></p><p></p><p><i><br>
Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors </i><b><i>will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. </i></b><i>The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.</i></p></div>

AI/ML Engineer

Techionik Ltd

<p>An <b>AI/ML Engineer</b> is responsible for designing, developing, and deploying machine learning models and artificial intelligence systems that solve real-world problems. The role involves working with large datasets, building predictive models, optimizing algorithms, and integrating ML solutions into production environments. AI/ML Engineers work closely with data scientists, software engineers, and product teams to deliver scalable and efficient AI-driven applications.</p><p><b>Key Responsibilities</b></p><ul><li>Develop, train, test, and deploy machine learning and deep learning models.</li><li>Collect, preprocess, and analyze large datasets for model training and evaluation.</li><li>Research and implement cutting-edge ML algorithms and techniques.</li><li>Build end-to-end ML pipelines (data ingestion &rarr; model training &rarr; evaluation &rarr; deployment).</li><li>Optimize model performance (accuracy, latency, scalability).</li><li>Collaborate with data scientists to translate business problems into ML solutions.</li><li>Integrate ML models into production systems using APIs, cloud services, or MLOps tools.</li><li>Monitor, maintain, and retrain models in production to ensure long-term performance.</li><li>Document model architecture, data workflow, and implementation details.</li></ul><p><b>Required Skills</b></p><ul><li>Strong experience with <b>Python</b> and ML libraries (TensorFlow, PyTorch, Scikit-learn).</li><li>Proficiency in <b>data processing tools</b> (Pandas, NumPy, Spark).</li><li>Knowledge of <b>statistics</b>, <b>probability</b>, and <b>linear algebra</b>.</li><li>Experience with <b>machine learning algorithms</b> (regression, classification, NLP, CV, deep learning, etc.).</li><li>Familiarity with <b>cloud platforms</b> such as AWS, GCP, or Azure.</li><li>Understanding of <b>MLOps tools</b> (MLflow, Kubeflow, Docker, Kubernetes, CI/CD).</li><li>Strong problem-solving and analytical skills.</li></ul><p><b>Preferred Qualifications</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Data Science, or related field.</li><li>Experience with <b>big data technologies</b> (Hadoop, Spark).</li><li>Hands-on experience with <b>LLM integration</b> or <b>generative AI</b>.</li><li>Ability to build scalable ML architectures and work with REST APIs or microservices.</li></ul><p><b>Soft Skills</b></p><ul><li>Excellent communication and collaboration skills.</li><li>Ability to work in cross-functional teams.</li><li>Strong attention to detail and documentation.</li><li>Creative thinking and innovation mindset.</li></ul><p>Job Type: Full-time</p><p>Work Location: In person</p>

VLINQ DIGITAL (PRIVATE) LIMITED

<p>We are looking for a skilled and innovative <b>AI/ML Engineer</b> to design, develop, and deploy machine learning models and AI-driven solutions. The ideal candidate will work on data-driven projects, collaborate with cross-functional teams, and help integrate AI technologies into existing systems and products.</p><p><b>Key Responsibilities:</b></p><ul><li>Design, build, and deploy <b>machine learning models</b> for real-world applications.</li><li>Perform <b>data preprocessing, cleaning, and feature engineering</b>.</li><li>Evaluate and fine-tune model performance using <b>ML metrics and validation techniques</b>.</li><li>Collaborate with <b>data scientists, software engineers, and product teams</b>.</li><li>Implement <b>AI models into production</b> using APIs and automation pipelines.</li><li>Research and experiment with <b>new algorithms and frameworks</b>.</li><li>Document processes, model architectures, and deployment strategies.</li></ul><p><b>Requirements:</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in <b>Computer Science, Data Science, AI, or a related field</b>.</li><li><b>2&ndash;4 years of hands-on experience</b> in machine learning and AI development.</li><li>Strong programming skills in <b>Python</b> and familiarity with <b>TensorFlow, PyTorch, Scikit-learn, or Keras</b>.</li><li>Experience with <b>data manipulation libraries</b> (NumPy, Pandas) and <b>visualization tools</b> (Matplotlib, Seaborn).</li><li>Understanding of <b>ML algorithms, deep learning, NLP, or computer vision</b>.</li><li>Experience deploying models using <b>AWS, Azure, or Google Cloud AI services</b>.</li></ul><p>Job Type: Full-time</p><p>Work Location: In person</p>

<div></div><div><div><div><div><ul><div>5 - 7 Years</div>
<div></div><div>12 Openings</div>
 <div>Noida</div></ul></div><p></p><div><br>
<div><div>
</div></div></div></div><div></div><div><h3 class="jobSectionHeader"><b>Role description</b></h3>
<div><p>Role Proficiency:</p>
<p>
Under guidance from Senior ML Engineers develop ML models that provides accurate results with controls to solve the business problem identified using state of art techniques.</p>
<p>
Outcomes:</p>
<div>
<ul><li> Executes relevant data wrangling activities related to the problem in order to create dataset</li></ul>
<ul><li> Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem</li></ul>
<ul><li> Fine tune the baseline model for optimum performance</li></ul>
<ul><li> Test Models internally per acceptance criteria from business</li></ul>
<ul><li> Document relevant Artefacts for communicating with the business</li></ul>
<ul><li> Work with data scientists to deploy the models.</li></ul>
<ul><li> Work with product teams in planning and execution of new product releases.</li></ul>
<ul><li> Set OKRs and success steps for self/ team and provide feedback to goals for team members</li></ul>
<ul><li> Work with cross functional teams - business technology and product teams to understand the product vision; building ML solutions that provides value to the product</li></ul>
</div>
<p></p><p>Measures of Outcomes:</p>
<div>
<ul><li> Selection of the appropriate approach to the problem</li></ul>
<ul><li> Number of successful deployments of the model with optimised accuracy for baseline model</li></ul>
<ul><li> Adherence to project schedule / timelines</li></ul>
<ul><li> Personal and team achievement of quarterly/yearly objectives (OKR Assignments HIG Stretch goals)</li></ul>
</div>
<p></p><p>Outputs Expected:</p>
<p>
Design to deliver Product Objectives:</p>
<div>
<ul><li>Design ML solutions which are aligned to and achieve product objectives
</li></ul><ul><li>Define data requirements for the model building and model monitoring; working with product managers to get necessary data</li></ul></div><br>
<p><br>
Updated on state of art techniques in the area of AI / ML :</p>
<div>
<ul><li>Perform necessary research using the latest and state of art techniques to design scalable approaches</li></ul>
<ul><li>Explain the relevance of the technologies<br>
its pros and cons to the product team; enabling accurate design experiences</li></ul>
</div>
<p></p><p>Skill Examples:</p>
<div>
<ul><li> Technically strong with the ability to connect the dots</li></ul>
<ul><li> Ability to communicate the relevance of technology to the stakeholders in a simple relatable language</li></ul>
<ul><li> Curiosity to learn more about new business domains and Technology Innovation</li></ul>
<ul><li> An empathetic listener who can give and receive honest thoughtful feedback</li></ul>
</div>
<p></p><p>Knowledge Examples:</p>
<ul>
<li> Expertise in machine learning model building lifecycle
<div> <ul><li>Clear understanding of various ML techniques with appropriate use to business problems</li></ul>
<ul><li> A strong background of statistics and Mathematics</li></ul>
<ul><li> Expertise in one of the domains &ndash; Computer Vision Language Understanding or structured data</li></ul>
<ul><li> Experience in executing collaboratively with engineering design user research teams and business stakeholders</li></ul>
<ul><li> Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions</li></ul>
<ul><li> Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe</li></ul>
<ul><li> Familiar with the machine learning model testing approaches</li></ul>
<ul><li> A genuine eagerness to work and learn from a diverse and talented team</li></ul></div><br>
<p></p>Additional Comments:
<p></p>
<p>Role : ML Engineer I Band : B1 Location : Noida</p>
</li>
</ul></div><h3 class="jobSectionHeader"><b>Skills</b></h3>
<div><p>Machine Learning,Software Engineering,Automation</p></div></div></div></div><p></p>
<br><div><h3 class="jobSectionHeader"><b>About UST</b></h3>
<div>UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div></div>

ML Engineer I

Altak Group

<p><b>Responsibilities</b></p><ul><li>Design, build, and deploy complete AI/ML systems from experimentation to production.</li><li>Work with LLMs, neural networks, RAG pipelines, agentic AI frameworks, and scalable data workflows.</li><li>Partner with product and engineering teams to prototype and ship several AI-driven features and products each month.</li><li>Optimize models for performance, scalability, cost efficiency, and real-world constraints.</li><li>Provide production support for deployed models and continuously iterate to improve outcomes.</li><li>Stay ahead of emerging AI technologies and integrate new tools to accelerate development cycles.</li></ul><p><b>Qualifications</b></p><ul><li>4+ years of hands-on experience in ML engineering or applied data science.</li><li>Strong expertise with LLMs, neural networks, RAG architecture, and agent-based AI systems.</li><li>Solid background in data pipeline engineering, ETL, orchestration, and distributed processing.</li><li>Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.</li><li>Familiarity with modern AI stacks, including LangChain, Hugging Face, vector databases, and related tools.</li><li>Proven experience deploying ML systems in cloud environments such as AWS, Azure, or GCP.</li><li>Strong analytical thinking, problem-solving mindset, and ability to thrive in iterative, high-velocity product cycles.</li><li>Bonus: Experience shipping multiple AI products within short development timelines.</li></ul><p>Job Type: Full-time</p><p>Pay: Rs300,000.00 - Rs400,000.00 per month</p><p>Application Question(s):</p><ul><li>Walk me through the most complex AI/ML system you&rsquo;ve built end-to-end. What problem did it solve, what stack did you use, and what specifically was your contribution?</li><li>Have you deployed an LLM, RAG pipeline, or agentic workflow into production? Describe the architecture, latency constraints, and how you handled scalability or cost optimization.</li><li>Explain a time you optimized a model or data pipeline for performance. What metrics improved and how did you achieve it?</li><li>Tell me about a recent AI framework, tool, or technique you adopted that significantly accelerated your delivery. Why did you choose it and what impact did it have?</li><li>You&rsquo;re tasked with shipping two AI-driven product features in a single month. What&rsquo;s your approach from discovery to deployment?</li><li>How much experience do you have with Rag Structure, LLM's, Vectorization?</li><li>Current salary</li><li>Desired salary</li><li>Notice Period Duration</li><li>Are you availabile for an online session to understand your background better between 10pm to 3am PKT ?</li></ul><p>Work Location: In person</p>

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