ml engineer

Ford Motor Company

<div>
 
 Job Description
 
 
 
 As a ML Engineer, you will be part of a high performing team working on exciting opportunities in AI/ML. We are looking for a highly skilled, technical, hands-on ML engineer with a solid background in building end-to-end AI/ML applications, exhibiting a strong aptitude for learning and keeping up with the latest advances in AI/ML.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop ML Platform to empower Data Scientists to perform end to end ML Ops.
 </li>
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 Work actively and collaborate with Data Science teams within Credit IT to design and develop end to end Machine Learning systems.
 </li>
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 Lead evaluation of design options, tools, and utilities to build implementation patterns for MLOps using VertexAI in the most optimal ways.
 </li>
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 Create solutions and perform hands-on PoCs.
 </li>
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 Work with Suppliers, Google Professional Services, and other Consultants as required.
 </li>
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 Collaborate with program managers to plan iterations, backlogs, and dependencies across all workstreams to progress the program at the required pace.
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 Collaborate with Data/ML Engineering architects, SMEs, and technical leads to establish best practices for data products needed for model training and monitoring considering regulatory policy and legal compliance.
 </li>
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 Develop end to end and scalable Generative AI solutions.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science or related field.
 </li>
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 8+ years of relevant work experience in solution, application, and ML engineering, DevOps with deep understanding of cloud hosting concepts and implementations.
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 5+ years of hands-on experience in Risk Analytics, MLOps and Engineering Solutions for ML based models.
 </li>
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 Knowledge of enterprise frameworks and technologies.
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 Strong in engineering design patterns, experience with secure interoperability standards and methods, engineering tools and processes.
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 Strong in containerization using Docker/Podman.
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 Strong understanding on DevOps principles and practices, including continuous integration and deployment (CI/CD), automated testing &amp; deployment pipelines.
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 Good understanding of cloud security best practices and be familiar with different security tools and techniques like Identity and Access Management (IAM), Encryption, Network Security, etc.
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 Understanding of microservices architecture.
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 Strong leadership, communication, interpersonal, organizing, and problem-solving skills.
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 Strong in AI Engineering
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 </ul>
</div>

ML Engineer

LimeoX LLC

<div>
 
 
 We&rsquo;re Hiring: AI/ML Engineer On-Site (Sargodha)
 
 
 
 
 
 
 We are looking for a&nbsp;
 
 highly skilled and independent AI/ML Engineer
 
 &nbsp;to join our growing team. You&rsquo;ll work on cutting-edge projects involving&nbsp;
 
 Large Language Models (LLMs), custom weightage models, clustering &amp; classification, automation, and AI-powered workflows
 
 .
 
 
 This role offers technical direction and project requirements, but you&rsquo;ll have the freedom to design and implement innovative solutions from scratch. If you enjoy building and experimenting with models, researching new approaches, and turning ideas into production-ready tools, this is the place for you.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Build and fine-tune weightage models and LLMs&nbsp;to solve real-world business problems.
 
 </li>
 <li>
 
 Develop custom prediction models&nbsp;and conduct comparative research to determine the most effective approach.
 
 </li>
 <li>
 
 Perform AI/ML research&nbsp;and translate innovative concepts into production-ready solutions.
 
 </li>
 <li>
 
 Design and implement AI agents and automations, including workflows integrated with Google Sheets/Docs via Apps Script.
 
 </li>
 <li>
 
 Apply clustering and classification techniques&nbsp;to identify patterns, generate insights, and support decision-making.
 
 </li>
 <li>
 
 Develop, optimize, and maintain data pipelines&nbsp;and system integrations for model training and deployment.
 
 </li>
 <li>
 
 Collect, scrape, and preprocess data&nbsp;for machine learning training, evaluation, and analysis.
 
 </li>
 <li>
 
 Deploy, monitor, and continuously retrain models&nbsp;to ensure optimal performance over time.
 
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 1-2 years of experience as an&nbsp;
 
 AI/ML Engineer
 
 &nbsp;or similar role.
 </li>
 <li>
 Strong Python skills with hands-on experience in&nbsp;
 
 ML frameworks
 
 &nbsp;(TensorFlow, PyTorch, scikit-learn).
 </li>
 <li>
 Experience with&nbsp;
 
 Weightage-based algorithms
 
 &nbsp;and&nbsp;
 
 LLM fine-tuning
 
 .
 </li>
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 Solid understanding of&nbsp;
 
 clustering
 
 &nbsp;and&nbsp;
 
 classification
 
 &nbsp;techniques.
 </li>
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 Proficiency in&nbsp;
 
 automation via Google Apps Script
 
 .
 </li>
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 Knowledge of&nbsp;
 
 web scraping
 
 &nbsp;tools (e.g., Selenium, Playwright).
 </li>
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 Experience with databases (PostgreSQL, MySQL, MongoDB).
 </li>
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 Familiarity with&nbsp;
 
 asynchronous programming
 
 &nbsp;and multi-threading.
 </li>
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 Strong research skills and ability to work independently.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Degree in&nbsp;
 
 Computer Science, AI, Data Science, or a related field
 
 .
 </li>
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 Experience with&nbsp;
 
 cloud AI platforms
 
 &nbsp;(AWS SageMaker, Google Vertex AI, Azure ML).
 </li>
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 Contributions to&nbsp;
 
 open-source AI projects
 
 .
 </li>
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 Knowledge of&nbsp;
 
 MLOps practices
 
 .
 </li>
 </ul>
 
 
 
 
 
 Salary &amp; Perks
 
 
 <ul>
 <li>
 
 Starting salary:
 
 &nbsp;100,000 &ndash; 150,000 PKR (depending on skills &amp; experience).
 </li>
 <li>
 
 Accommodation
 
 </li>
 <li>
 
 Travel Allowance
 
 </li>
 <li>
 
 Provident Fund
 
 </li>
 </ul>
 
 
 
 
 
 Ready to innovate with AI?
 
 &nbsp;Apply now and help shape the future of intelligent automation at LimeoX.
 
 
 
 
 
 
 Note: This is an on-site position. Please apply only if you can relocate to the job location and are not seeking remote work options.
 
 
</div>

AI/ML Engineer

Adescare technology

We are Hiring | Senior AI / ML Engineer (LLM | RAG | On-Prem AI)We are looking for a Senior AI/ML Engineer (5&ndash;7 years) with strong hands-on experience in building fully on-premise AI solutions (no external cloud APIs). The role involves working on private LLMs, RAG pipelines, document intelligence, and AI-powered regulatory solutions.Location: Sohna Road, Gurgaon (Onsite)Notice Period: Immediate to 15 DaysContract: 3 Months (Extendable up to 6 Months based on need)Budget: Up to 20 LPAKey Skills Required:<ul><li>Python, NLP, Transformers (HuggingFace)</li><li>Self-hosted LLM fine-tuning &amp; prompt engineering</li><li>RAG pipelines, embeddings, FAISS / ChromaDB</li><li>PDF parsing, OCR, document comparison &amp; summarization</li><li>FastAPI, Docker, Kubernetes, Linux</li><li>On-prem or private cloud deployment, GPU optimization</li></ul>Job Type: Contractual / Temporary Contract length: 6 monthsPay: &#8377;1,000,000.00 - &#8377;2,000,000.00 per yearBenefits:<ul><li>Health insurance</li><li>Provident Fund</li></ul>Work Location: In person

MAERSK

<div>Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyze data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modeling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions.
We are an ambitious data product team and are looking for a AI/ML Engineer to join us in our journey!
Let us start by introducing ourselves and then move on to you and your potential new role.
<h2 class="jobSectionHeader">The team - who are we
</h2>We are an ambitious data product team of diverse problem-solvers with a drive for getting the job done, and a shared passion to use data, data science (DS), machine learning (ML) and engineering excellence to make a difference for our customers.
Concretely, we develop data products for the Maersk.com platform for our internal and external customers.
We are a team, not a collection of individuals. We value our diverse backgrounds, our different personalities and strengths &amp; weaknesses. We value trust and passionate debates. We challenge each other and hold each other accountable. We uphold a caring feedback culture to help each other grow, professionally and personally.
<h2 class="jobSectionHeader">Our new member - who are you
</h2>You are passionate about cracking hard business problems with data science and ML excellence . You combine business acumen and a drive for impact with hands‑on model development and experimentation to create data products that matter .
You are a go‑getter, a challenger, learner, collaborator and shaper. Your curiosity might lead you right after reading this posting to Maersk.com to explore one of our (and your potential future) channels of impact from the user perspective.
You are, like us, a team player who cares about your team members, about growing professionally and personally, about helping your team mates grow, and about having fun together.
If this so far speaks to you, you should absolutely read on for more details.
<h2 class="jobSectionHeader">About the role
</h2>As AI/ML Engineer , you will be part of our cross‑functional data product team , developing ML‑powered applications for our Maersk.com platform based on strong scientific rigor and engineering principles. You will collaborate closely with our colleagues from the Maersk.com platform.
The data we work with is collected and validated from various streams and used to develop sophisticated ML models (e.g., segmentation, recommender systems, ranking, propensity).
You&rsquo;ll contribute across the full model lifecycle : problem framing, feature engineering, modeling, evaluation, deployment, online experimentation (A/B tests) , and production monitoring .
<h2 class="jobSectionHeader">Your responsibilities include
</h2><ul><li>Frame problems and define outcomes : Translate customer/business objectives into clear DS problems with measurable success metrics.
</li><li>Build production‑grade models : Design, train, and validate models for both batch scoring and real‑time inference .
</li><li>Feature engineering at scale : Partner with data engineers to design robust feature pipelines , feature stores, and data contracts for reliable online/offline parity.
</li><li>Experimentation &amp; causal measurement : Design and run A/B tests , multi‑armed bandits, and holdout analyses; ensure rigorous statistical evaluation, guardrails, and risk controls.
</li><li>MLOps &amp; model lifecycle : Use model registries, CI/CD, automated evaluations, drift/decay monitoring, and canary rollouts to deploy safely and iterate quickly.
</li><li>Documentation &amp; reproducibility : Keep experiments, datasets, and models well‑documented and reproducible; champion high‑quality scientific and engineering practices.
</li><li>Cross‑functional collaboration : Work closely with product, platform engineering, and analytics to align on customer outcomes , explain model behavior, and communicate trade‑offs to non‑technical audiences.
</li><li>Responsible AI : Consider fairness, bias, explainability, privacy, and compliance when designing and deploying models.
</li><li>Continuous improvement : Independently direct your time and resources with engineers and fellow data scientists in the team; contribute to transforming how we work as part of our broader cultural transformation.
</li></ul><h2 class="jobSectionHeader">Skills &amp; experience we are looking for
</h2><ul><li>Education : Bachelor&rsquo;s degree, ideally in computer science, statistics, mathematics, engineering, or a related field. The ideal person may possess an advanced degree focusing on ML, applied statistics, or distributed systems.
</li><li>Experience : 4&ndash;6 years industry experience in data science or ML engineering within a software or analytics‑intensive B2B environment, delivering models into production as part of a product team.
</li><li>ML expertise : Solid understanding and experience with batch and real‑time ML solutions , especially personalization, recommendations, ranking, and propensity modeling at scale.
</li><li>Languages &amp; tooling : Strong hands‑on skills in Python and SQL . Experience with PySpark/Spark , and ML libraries such as scikit‑learn , TensorFlow , PyTorch , and XGBoost/LightGBM .
</li><li>Data &amp; platforms : Working knowledge of Databricks , Spark Structured Streaming , feature stores , experiment platforms, and MLflow/model registries .
</li><li>Cloud &amp; infrastructure : Familiarity with Azure, GCP, or AWS ; containerization and orchestration ( Docker, Kubernetes ) and pub/sub systems (e.g., Kafka ) for real‑time features/inference.
</li><li>Experimentation &amp; statistics : Experience designing and analyzing A/B tests , understanding of confidence intervals, power, uplift, and common pitfalls (e.g., peeking, interference).
</li><li>Data product mindset : Ability to compellingly present technical topics to non‑technical audiences; strong problem‑solver and self‑starter comfortable navigating ambiguity.
</li></ul><h2 class="jobSectionHeader">Good to have / we value familiarity with:
</h2><ul><li>CI/CD , DevOps, microservices, monitoring, git and source control, effective documentation; insight sharing; data modeling (dimensional/BI), ETL , data quality; responsible AI and model observability.
</li></ul><h2 class="jobSectionHeader">About the company
</h2>A.P. Moller - Maersk is the globally leading integrated container logistics company and responsible for moving 20% of global trade every year. Our over 80,000 employees work across 130 countries to connect and simplify global trade, and help our customers grow and thrive. We are right now driving an industry-defining data and technology transformation that is enabling us to deliver value to our customers with best-in-class technology, data &amp; data products. This is a unique opportunity to further grow your career within data and technology in an iconic company with Danish roots and global reach.
<h2 class="jobSectionHeader">What we offer
</h2>This position offers a great opportunity to apply and further develop your cutting-edge knowledge of data science and machine learning to create results and insights that are transforming the transport and logistics industry. Believe us - there has never been a more exciting time to be part of the data &amp; technology area in the shipping &amp; logistics industry!
Our team is embracing a flexible hybrid work setup, where we like to work from home, and equally much like to meet weekly together in the office. 
 
As a AI/ML Engineer with Maersk, you will be part of the community of data &amp; engineering practitioners across the company, where we develop the foundations of our future business.
We operate in a fast-paced environment utilizing modern technologies.
We embrace innovation methods where we have a close dialogue with end users, make early use of mock-ups &amp; POCs and are committed to incremental development.
We value customer outcomes and are passionate about using technology to solve problems.
We are a diverse team with colleagues from different backgrounds and cultures.
We offer the freedom, and responsibility, to shape the setup and the processes we use in our community.
We support continuous learning, including through conferences, workshops and meetups.
Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. 
We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com .
CORE SKILLS Data Analysis: The process of inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making Proficiency Level: Proficient Statistical Analysis: The process of collecting and analyzing data to identify patterns and trends, and to make informed decisions. Proficiency Level: Proficient AI &amp; Machine Learning: The field of artificial intelligence (AI) involves creating systems that can perform tasks that typically require human intelligence. Machine learning (ML) is a subset of AI that uses algorithms to learn from and make predictions based on data Proficiency Level: Proficient Programming: Writing code to manipulate, analyze, and visualize data, often using languages like Python, R, and SQL. Proficiency Level: Proficient Data Science: A multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Proficiency Level: Proficient SPECIALIZED SKILLS Data Validation and Testing: Ensuring that data is accurate and meets the required standards before it is used in analysis or decision-making. Model Deployment: The process of making a trained machine learning model available for use in production environments. Machine Learning Pipelines: Automated workflows that manage the end-to-end process of training and deploying machine learning models. Deep Learning: A subset of machine learning involving neural networks with many layers, used to model complex patterns in data. Natural Language Processing (NLP): A field of AI that focuses on the interaction between computers and humans through natural language. Optimization &amp; Scientific Computing: Using Mathematical techniques and computational algorithms to solve complex problems and optimize processes Decision Modeling and Risk Analysis: Decision Modeling and Risk Analysis are methodologies used to make informed, data-driven decisions under uncertainty, especially when multiple factors and possible outcomes need to be considered. Technical Documentation: Creating and maintaining documentation that explains the functionality, use, and maintenance of software or systems. Definition of Proficiency Levels: Foundational: This is the entry level of the skill, typically expected when starting a new role or working with the skill for the first time. You rely on strong manager support, coaching, and training as you build the capability to progress to higher proficiency levels. Proficient: This is the level at which you are considered effective in the skill. You demonstrate more than just functional competence&mdash;you begin to have a noticeable impact in your role by applying the skill consistently and meaningfully. You require only minimal support, coaching, or training to apply the skill successfully. Advanced: This is the level where you move beyond meeting expectations to actively leading, influencing, and delivering considerable impact across the wider business. You are seen as a role model, demonstrate the skill independently, and require little to no manager support.</div>

Nissan

Nissan is a pioneer in Innovation and Technology. With a focus on Mobility, Operational Excellence, Value to our Customers and Electrification of vehicles, you can expect to be part of a very exciting journey here at Nissan. 
 
Nissan is going after a massive Digital Transformation backed by leading technologies across the organization globally. We are committed to building a diverse, entrepreneurial organization, and our current team is a strong evidence of that. Our people are what drive the business forward. At Nissan Digital, you will be part of a dynamic team with ample opportunities to grow and make a difference. 
 
Responsibilities: 
Assist in developing, training, and optimizing machine learning models for various applications. 
Work with large datasets, performing data preprocessing, feature engineering, and model evaluation. 
Collaborate with data scientists and software engineers to integrate ML models into production environments. 
Conduct experiments to improve model accuracy and efficiency. 
Write clean, efficient, and well-documented code for ML model development. 
Stay updated with the latest advancements in ML algorithms and technologies. 
 
Key Competencies: 
Strong analytical and problem-solving skills. 
Ability to understand and implement ML algorithms effectively. 
Good communication skills to collaborate with cross-functional teams. 
Attention to detail and a structured approach to work. 
GenAI: Curiosity and experimentation with LLMs &amp; GenAI tools (e.g., ChatGPT, Gemini) and prompt tuning 
MLOps: Learning foundations of model deployment, version control, and experiment tracking 
 
Relevant Work Exp : 2-5 years 
 
Technical Skills: 
Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn. 
Experience with data manipulation using Pandas and NumPy. 
Familiarity with cloud platforms like AWS, Azure, or GCP for ML model deployment. 
Knowledge of SQL and database management. 
Understanding of software development best practices (Git, Docker, CI/CD). 
 
Behavioral Competencies: 
Adaptability: Open to learning and applying new ML techniques, tools, and frameworks. 
Learning Agility: Willingness to experiment, analyze failures, and continuously improve skills. 
Teamwork: Works collaboratively with peers, takes feedback constructively, and contributes to team success. 
 
Certifications (Optional): 
TensorFlow Developer Certification 
AWS Certified Machine Learning - Specialty 
Microsoft Certified: Azure AI Engineer Associate 
Google Professional Machine Learning Engineer 
Trivandrum Kerala India

ML Engineer II

Varishtha Infotech

Minimum Experience: 4 years (mandatory)CTC Budget: &#8377;18&ndash;20 LPA (strict, no exceptions)Location: Madhapur, HyderabadWork mode: Work From OfficeNotice period: Immediate to 15daysMandatory Skill:<ul><li>Strong hands-on proficiency in Python for production-level ML development</li></ul>Good to Have:<ul><li>Experience with NVIDIA technologies (Jetson / CUDA / TensorRT / GPU-based inference)</li></ul>Qualifications&#9679; Strong background in AI/ML with applied experience in computer vision, robotics ML, or real-time edge intelligence. &#9679; Hands-on experience with NVIDIA GPU acceleration, CUDA, TensorRT, and deep learning frameworks (e.g., PyTorch, TensorFlow). &#9679; Proficiency in Python, Linux, and modern development workflows (Git, CI/CD, etc.). &#9679; Experience building, training, and deploying ML models in production or on embedded systems. &#9679; Familiarity with robotic perception concepts such as object detection, segmentation, tracking, sensor fusion, or pose estimation. &#9679; Ability to analyze performance bottlenecks and optimize models for latency, throughput, and reliability on embedded hardware. &#9679; Strong cross-functional collaboration skills with software, hardware, and robotics teams. &#9679; Ability to work full-time at our HQ in Pasadena, CA.Desired Multipliers&#9679; Experience with NVIDIA tools and frameworks for robotics and edge AI (e.g., Isaac, TensorRT, Jetson ecosystem). &#9679; Familiarity with ROS (Robot Operating System). &#9679; Experience with perception algorithms, sensor fusion, motion planning, or behavior modeling. &#9679; Knowledge of reinforcement learning, imitation learning, or behavior cloning for robotic applications. &#9679; Experience working in noisy, dynamic, or unstructured real-world environments. &#9679; Experience with agile tools such as JIRA. &#9679; Strong attention to detail and a passion for improving real-world robotic performance.Responsibilities&#9679; Build and maintain data pipelines for continuous model training, evaluation, and deployment. &#9679; Optimize models for real-time inference on embedded GPU hardware (e.g., NVIDIA Jetson). &#9679; Improve the system&rsquo;s ability to handle challenging conditions such as heat, steam, occlusion, variable lighting, and rapid operator movements. &#9679; Develop ML systems to support tasks such as activity recognition, anomaly detection, quality assessment, and robotic behavior prediction. &#9679; Implement monitoring and feedback loops to identify model drift and drive continuous improvement.Job Types: Full-time, PermanentPay: &#8377;1,500,000.00 - &#8377;2,000,000.00 per yearAbility to commute/relocate:<ul><li>Hyderabad, Telangana (500099): Reliably commute or planning to relocate before starting work (Required)</li></ul>Application Question(s):<ul><li>Notice period</li><li>Current CTC</li><li>Expected CTC</li></ul>Experience:<ul><li>production-level ML development with python: 4 years (Required)</li><li>NVIDIA GPU acceleration: 3 years (Required)</li><li>CUDA, TensorRT, and deep learning frameworks: 3 years (Required)</li><li>Git, CI/CD: 3 years (Required)</li></ul>Work Location: In person

HDFC Bank

<div>
 
 
 Job Purpose:
 
 
 
 An experienced AI/ML Engineer to design, develop and maintain AI / ML and GenAI based solutions on enterprise platform on Industry best and open-source models at scale along with governance and security frameworks
 
 
 
 
 
 
 Desired Skills :
 
 
 <ul>
 <li>
 Strong background in designing and implementing machine learning and deep learning algorithms and responsible AI practices at enterprise scale and speed
 </li>
 <li>
 Working knowledge with ML platforms like TensorFlow, PyTorch, or Hugging Face
 </li>
 <li>
 Proficiency in Training, Tuning and Deploying GenAI models based on LLMs, GANs, and VAEs
 </li>
 <li>
 Hands on expert in programming languages like Python, Java, or C++, and have experience with cloud platforms, containerization technologies (e.g., Docker, Kubernetes), and data pipeline tools (e.g., Apache Kafka, Spark)
 </li>
 <li>
 Experience working in cross-functional teams
 </li>
 <li>
 Strong analytical and problem solving skills
 </li>
 </ul>
</div>

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